test(e2e): add coverage registry and collector (#32304)

Introduce the e2e coverage denominator: 282 behavior cells across the six
tracking modules (LLMs, MCPs, Management/UI, Reliability & Performance,
Logging & Guardrails, Other), one validated YAML row each, plus a collector
that diffs the registry against @pytest.mark.covers markers and reports
coverage per module.

The registry rows validate against a pydantic discriminated union so a row
cannot carry a field from another module. The collector is static: a
collect-only pass reads the markers, so it runs no test and needs no live
proxy. Register the covers marker suite-wide so that pass works under
--strict-markers.

This is a draft for review. Tiers are proposed rather than signed off, and a
few cells still need a support check or a prune.
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@ -33,6 +33,10 @@ def pytest_configure(config: pytest.Config) -> None:
"markers",
"e2e: live test that requires a running proxy and real provider keys",
)
config.addinivalue_line(
"markers",
"covers(cell_id, *, exercised_on=()): coverage-registry cell(s) this test covers",
)
def _liveness_reason(label: str, base_url: str) -> str | None:

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@ -0,0 +1,55 @@
# e2e coverage registry
This directory is the **denominator** for e2e test coverage: the set of behaviors we
want covered, one row per behavior, checked into the repo so coverage is a number we
can track instead of a guess. It implements the plan in the "E2E Coverage Tracking"
note; the naming grammar lives in `tests/e2e/CLAUDE.md`.
## The model
A **cell** is one customer-noticeable behavior a single e2e test can assert pass/fail
on, for example `llm.chat_completions.bedrock_converse.tool_use.stream.works`. Cells are
grouped `module > feature > test`, six dashboard modules in all. Each cell carries a
tier (P0/P1/P2), a source, and a `fail_before_fix` flag.
The rows live in per-prefix YAML files (`llm_*.yaml`, `mgmt.yaml`, `mcp.yaml`,
`reliability.yaml`, `logging.yaml`, `guardrail.yaml`, `other.yaml`) and validate against
the discriminated union in `schema.py`, so an LLM row cannot carry a guardrail field and
vice versa. `logging` and `guardrail` are two id-prefixes that roll up into the single
"Logging & Guardrails" dashboard module.
A test declares what it covers with a marker:
```python
@pytest.mark.covers("llm.chat_completions.openai.tool_use.stream.works")
def test_openai_streaming_tool_calls(self) -> None:
...
```
## The number
`collector.py` diffs the registry against those markers and reports coverage per module.
It is static: a collect-only pass reads the markers, so it runs no test and needs no live
proxy. Whether a covered cell currently passes or fails is a separate, live concern.
```
cd tests/e2e && PYTHONPATH=. python -m coverage_registry.collector
```
The headline is P0 coverage. The collector also lists markers that point at ids not in
the registry, so a typo or an unenumerated behavior surfaces instead of being silently
dropped.
## Status: this is a draft for review
The cells were enumerated from the codebase and the tiers are a first proposal. Known
things to settle before treating the set as final:
- tiers are proposed, not signed off; 125 P0 is a lot to prove fail-before-fix, so P0 may
want tightening
- a few cells need a support check or a prune (for example `llm.embeddings.anthropic.*`
and `reliability.perf.throughput.under_slo`)
- auth is covered in two places (`other.auth.*` and the mgmt authz assertions); the
boundary needs a decision, and the auth cluster may deserve promotion to its own module
- the P2 "niche" cells each stand in for a large tail of integrations/providers by design,
so the denominator is deliberately P0-weighted rather than a full inventory

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@ -0,0 +1,8 @@
"""The e2e coverage registry: the denominator for e2e test coverage.
`schema.py` defines one validated row per customer-noticeable behavior (a "cell").
The `*.yaml` files hold the rows, one file per id-prefix. `registry.py` loads and
validates them; `collector.py` diffs the registry against the `@pytest.mark.covers`
markers on the live tests and reports coverage per module. See tests/e2e/CLAUDE.md
for the naming grammar.
"""

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@ -0,0 +1,156 @@
"""Diff the registry (denominator) against the @pytest.mark.covers markers on the
live tests (numerator) and report coverage per module.
Coverage here is static: it reads the markers via a collect-only pass, so it runs
no test and needs no live proxy. Whether a covered cell currently passes or fails
(covered_pass vs covered_fail) is a separate, live concern layered on top later.
cd tests/e2e && PYTHONPATH=. python -m coverage_registry.collector
"""
from __future__ import annotations
import contextlib
import io
import sys
from dataclasses import dataclass
from pathlib import Path
import pytest
from .registry import load_registry
from .schema import MODULE_ORDER, ROLLUP, Cell, Tier
E2E_DIR = Path(__file__).resolve().parent.parent
class _CoversSink:
"""Pytest plugin: after collection, capture every cell id declared via
@pytest.mark.covers(...), plus any nodes that failed to import."""
def __init__(self) -> None:
self.covered_ids: frozenset[str] = frozenset()
self.collection_errors: tuple[str, ...] = ()
def pytest_collection_finish(self, session: pytest.Session) -> None:
self.covered_ids = frozenset(
arg
for item in session.items
for marker in item.iter_markers(name="covers")
for arg in marker.args
if isinstance(arg, str)
)
def pytest_collectreport(self, report: pytest.CollectReport) -> None:
if report.failed:
self.collection_errors = (*self.collection_errors, report.nodeid)
def collect_covered_ids(e2e_dir: Path = E2E_DIR) -> tuple[frozenset[str], tuple[str, ...]]:
"""Return (covered cell ids, nodeids that failed to import)."""
sink = _CoversSink()
with contextlib.redirect_stdout(io.StringIO()):
pytest.main(
["--collect-only", "-qq", "--continue-on-collection-errors", "-p", "no:cacheprovider", str(e2e_dir)],
plugins=[sink],
)
return sink.covered_ids, sink.collection_errors
@dataclass(frozen=True, slots=True)
class ModuleCoverage:
module: str
total: int
covered: int
p0_total: int
p0_covered: int
@dataclass(frozen=True, slots=True)
class CoverageReport:
modules: tuple[ModuleCoverage, ...]
total: int
covered: int
p0_total: int
p0_covered: int
p0_gaps: tuple[str, ...]
orphan_markers: tuple[str, ...]
collection_errors: tuple[str, ...]
def _module_coverage(module: str, cells: tuple[Cell, ...], covered: frozenset[str]) -> ModuleCoverage:
in_module = tuple(c for c in cells if ROLLUP[c.module] == module)
p0 = tuple(c for c in in_module if c.tier is Tier.P0)
return ModuleCoverage(
module=module,
total=len(in_module),
covered=sum(1 for c in in_module if c.id in covered),
p0_total=len(p0),
p0_covered=sum(1 for c in p0 if c.id in covered),
)
def compute_coverage(
cells: tuple[Cell, ...],
covered: frozenset[str],
collection_errors: tuple[str, ...] = (),
) -> CoverageReport:
p0_cells = tuple(c for c in cells if c.tier is Tier.P0)
registry_ids = frozenset(c.id for c in cells)
return CoverageReport(
modules=tuple(_module_coverage(m, cells, covered) for m in MODULE_ORDER),
total=len(cells),
covered=sum(1 for c in cells if c.id in covered),
p0_total=len(p0_cells),
p0_covered=sum(1 for c in p0_cells if c.id in covered),
p0_gaps=tuple(sorted(c.id for c in p0_cells if c.id not in covered)),
orphan_markers=tuple(sorted(covered - registry_ids)),
collection_errors=collection_errors,
)
def _row(label: str, covered: int, total: int, p0_covered: int, p0_total: int) -> str:
frac = f"{covered}/{total}"
p0 = f"{p0_covered}/{p0_total}"
return f"{label:30}{frac:>12}{p0:>14}"
def render(report: CoverageReport) -> str:
rows = tuple(_row(m.module, m.covered, m.total, m.p0_covered, m.p0_total) for m in report.modules)
pct = (100.0 * report.p0_covered / report.p0_total) if report.p0_total else 0.0
lines = (
f"{'MODULE':30}{'COVERED':>12}{'P0 COVERED':>14}",
*rows,
"-" * 56,
_row("ALL", report.covered, report.total, report.p0_covered, report.p0_total),
"",
f"Headline (P0 coverage): {report.p0_covered}/{report.p0_total} ({pct:.1f}%)",
)
orphans = (
(
f"\n{len(report.orphan_markers)} marker(s) point at ids not in the registry "
f"(reconcile: fix the marker or add the cell):\n " + "\n ".join(report.orphan_markers),
)
if report.orphan_markers
else ()
)
warning = (
(
f"\nWARNING: {len(report.collection_errors)} node(s) failed to import during "
f"collection, so coverage may undercount:\n " + "\n ".join(report.collection_errors),
)
if report.collection_errors
else ()
)
return "\n".join((*lines, *orphans, *warning))
def main() -> int:
cells = load_registry()
covered, errors = collect_covered_ids()
print(render(compute_coverage(cells, covered, errors))) # noqa: T201 # CLI entrypoint output
return 0
if __name__ == "__main__":
sys.exit(main())

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@ -0,0 +1,29 @@
# Guardrail enforcement (behavior features). Grounded in litellm/proxy/guardrails/guardrail_hooks/.
# Rolls up into the "Logging & Guardrails" dashboard module together with logging.*
- {id: guardrail.presidio.pre_call.masks, module: guardrail, tier: P0, hook_point: pre_call, assertions: [masks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/presidio.py", rationale: "PII masking pre-call; data-leak blast radius"}
- {id: guardrail.presidio.post_call.masks, module: guardrail, tier: P0, hook_point: post_call, assertions: [masks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/presidio.py", rationale: "Mask PII in model output"}
- {id: guardrail.presidio.logging_only.masks, module: guardrail, tier: P0, hook_point: logging_only, assertions: [masks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/presidio.py", rationale: "Redact in logs without blocking"}
- {id: guardrail.bedrock.pre_call.blocks, module: guardrail, tier: P0, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/bedrock_guardrails.py", rationale: "AWS content guardrail blocks harmful input"}
- {id: guardrail.bedrock.during.blocks, module: guardrail, tier: P0, hook_point: during, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/bedrock_guardrails.py", rationale: "During-call moderation for streaming"}
- {id: guardrail.bedrock.post_call.blocks, module: guardrail, tier: P0, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/bedrock_guardrails.py", rationale: "Block harmful output"}
- {id: guardrail.lakera.pre_call.blocks, module: guardrail, tier: P0, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/lakera_ai_v2.py", rationale: "Prompt-injection block pre-execution"}
- {id: guardrail.lakera.post_call.blocks, module: guardrail, tier: P0, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/lakera_ai_v2.py", rationale: "Post-call injection on multi-turn chains"}
- {id: guardrail.openai_moderations.pre_call.blocks, module: guardrail, tier: P0, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/openai/moderations.py", rationale: "Content policy for regulated industries"}
- {id: guardrail.aim.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/aim/aim.py", rationale: "Security guardrail malicious-input"}
- {id: guardrail.aim.post_call.blocks, module: guardrail, tier: P1, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/aim/aim.py", rationale: "Output security check"}
- {id: guardrail.ibm_guardrails.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/ibm_guardrails/ibm_detector.py", rationale: "Enterprise multi-policy"}
- {id: guardrail.ibm_guardrails.post_call.blocks, module: guardrail, tier: P1, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/ibm_guardrails/ibm_detector.py", rationale: "Output policy validation"}
- {id: guardrail.semantic_guard.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/semantic_guard", rationale: "Semantic policy compliance"}
- {id: guardrail.block_code_execution.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/block_code_execution", rationale: "Code-injection prevention"}
- {id: guardrail.tool_permission.pre_call.allows, module: guardrail, tier: P1, hook_point: pre_call, assertions: [allows], exercised_on: [chat_completions], source: "guardrail_hooks/tool_permission.py", rationale: "Grant allowed tools"}
- {id: guardrail.tool_permission.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/tool_permission.py", rationale: "Block unauthorized tools"}
- {id: guardrail.microsoft_purview.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/microsoft_purview/purview_dlp.py", rationale: "DLP sensitive-data disclosure"}
- {id: guardrail.headroom.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/headroom/headroom.py", rationale: "Anomaly detection threshold"}
- {id: guardrail.generic_guardrail_api.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/generic_guardrail_api/generic_guardrail_api.py", rationale: "Vendor-agnostic custom API"}
- {id: guardrail.pangea.pre_call.blocks, module: guardrail, tier: P1, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/pangea/pangea.py", rationale: "API security + DLP"}
- {id: guardrail.niche_providers.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE cohort: lasso/hiddenlayer/model_armor/qualifire/guardrails_ai/cato/cisco/akto/prompt_security/promptguard/zscaler/vigil/etc"}
- {id: guardrail.niche_providers.post_call.blocks, module: guardrail, tier: P2, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE niche output filtering"}
- {id: guardrail.niche_providers.pre_call.allows, module: guardrail, tier: P2, hook_point: pre_call, assertions: [allows], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE niche allow-path passthrough"}
- {id: guardrail.tool_policy.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/tool_policy/tool_policy_guardrail.py", rationale: "Tool-use policy enforcement"}
- {id: guardrail.mcp_security.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [mcp_operations], source: "guardrail_hooks/mcp_security", rationale: "MCP protocol security"}
- {id: guardrail.llm_as_a_judge.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/llm_as_a_judge", rationale: "LLM-based judgment guardrail"}

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@ -0,0 +1,53 @@
# LLM conversational endpoints (chat_completions, messages, responses). Grounded in proxy handlers + model_prices json.
- {id: llm.chat_completions.openai.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py:8455", rationale: "Core endpoint/route/capability"}
- {id: llm.chat_completions.openai.basic.stream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: basic, streaming: stream, assertions: [works], source: "proxy_server.py:8455", rationale: "Core streaming"}
- {id: llm.chat_completions.openai.basic.nonstream.cost_logged, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: basic, streaming: nonstream, assertions: [works, cost_logged], source: "proxy_server.py:8455", rationale: "Cost logging regression catch"}
- {id: llm.chat_completions.openai.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "OpenAI function_calling; high usage"}
- {id: llm.chat_completions.openai.tool_use.stream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: tool_use, streaming: stream, assertions: [works], source: "model_prices json", rationale: "Tool calls over streaming"}
- {id: llm.chat_completions.openai.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "gpt-4o vision; high usage"}
- {id: llm.chat_completions.openai.prompt_cache_5m.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: openai, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Prompt caching cost optimization"}
- {id: llm.chat_completions.openai.thinking.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: thinking, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "o-series reasoning; emerging"}
- {id: llm.chat_completions.openai.structured_output.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: openai, capability: structured_output, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "response_schema extraction"}
- {id: llm.chat_completions.anthropic.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py:8455", rationale: "P0 route translated to Anthropic"}
- {id: llm.chat_completions.anthropic.basic.stream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: basic, streaming: stream, assertions: [works], source: "proxy_server.py:8455", rationale: "Streaming translation"}
- {id: llm.chat_completions.anthropic.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Claude tool_use; high usage"}
- {id: llm.chat_completions.anthropic.tool_use.stream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: tool_use, streaming: stream, assertions: [works], source: "model_prices json", rationale: "Streaming tool calls"}
- {id: llm.chat_completions.anthropic.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Claude vision; high usage"}
- {id: llm.chat_completions.anthropic.prompt_cache_5m.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: anthropic, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Claude prompt caching"}
- {id: llm.chat_completions.anthropic.thinking.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: anthropic, capability: thinking, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Claude extended thinking"}
- {id: llm.chat_completions.anthropic.structured_output.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: anthropic, capability: structured_output, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Claude response_schema"}
- {id: llm.chat_completions.bedrock_converse.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py:8455", rationale: "P0 route; Bedrock Converse unified"}
- {id: llm.chat_completions.bedrock_converse.basic.stream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: bedrock_converse, capability: basic, streaming: stream, assertions: [works], source: "proxy_server.py:8455", rationale: "Streaming over Converse"}
- {id: llm.chat_completions.bedrock_converse.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: bedrock_converse, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Converse function_calling; AWS adoption"}
- {id: llm.chat_completions.bedrock_converse.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: bedrock_converse, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Bedrock vision (Anthropic/Nova)"}
- {id: llm.chat_completions.bedrock_converse.prompt_cache_5m.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: bedrock_converse, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Anthropic-on-Bedrock caching"}
- {id: llm.chat_completions.bedrock_converse.thinking.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: bedrock_converse, capability: thinking, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Anthropic thinking on Bedrock"}
- {id: llm.chat_completions.vertex.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py:8455", rationale: "P0 route; Vertex AI"}
- {id: llm.chat_completions.vertex.basic.stream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: vertex, capability: basic, streaming: stream, assertions: [works], source: "proxy_server.py:8455", rationale: "Streaming over Vertex"}
- {id: llm.chat_completions.vertex.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: vertex, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Vertex Gemini function_calling"}
- {id: llm.chat_completions.vertex.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: vertex, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Gemini vision"}
- {id: llm.chat_completions.vertex.prompt_cache_5m.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: vertex, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Vertex Gemini prompt caching"}
- {id: llm.chat_completions.azure_openai.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py:8455", rationale: "P0 route; Azure OpenAI deployments"}
- {id: llm.chat_completions.azure_openai.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: chat_completions, route: azure_openai, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Azure OpenAI function_calling"}
- {id: llm.chat_completions.azure_foundry.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: chat_completions, route: azure_foundry, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py:8455", rationale: "Azure Foundry (azure_ai); newer, smoke"}
- {id: llm.messages.anthropic.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: basic, streaming: nonstream, assertions: [works], source: "anthropic_endpoints/endpoints.py:64", rationale: "Core endpoint; Anthropic Messages native"}
- {id: llm.messages.anthropic.basic.stream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: basic, streaming: stream, assertions: [works], source: "anthropic_endpoints/endpoints.py:64", rationale: "Streaming Messages API"}
- {id: llm.messages.anthropic.basic.nonstream.cost_logged, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: basic, streaming: nonstream, assertions: [works, cost_logged], source: "anthropic_endpoints/endpoints.py:64", rationale: "Cost logged on passthrough"}
- {id: llm.messages.anthropic.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Tool calls via Messages API"}
- {id: llm.messages.anthropic.tool_use.stream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: tool_use, streaming: stream, assertions: [works], source: "model_prices json", rationale: "Streaming tool calls"}
- {id: llm.messages.anthropic.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Vision via Messages API"}
- {id: llm.messages.anthropic.prompt_cache_5m.nonstream.works, module: llm, tier: P0, subject_endpoint: messages, route: anthropic, capability: prompt_cache_5m, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Prompt caching via Messages API"}
- {id: llm.messages.anthropic.thinking.nonstream.works, module: llm, tier: P1, subject_endpoint: messages, route: anthropic, capability: thinking, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Extended thinking via Messages API"}
- {id: llm.responses.openai.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: responses, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "response_api_endpoints/endpoints.py:26", rationale: "Core endpoint; OpenAI Responses native"}
- {id: llm.responses.openai.basic.stream.works, module: llm, tier: P0, subject_endpoint: responses, route: openai, capability: basic, streaming: stream, assertions: [works], source: "response_api_endpoints/endpoints.py:26", rationale: "Streaming via /v1/responses"}
- {id: llm.responses.openai.basic.nonstream.cost_logged, module: llm, tier: P0, subject_endpoint: responses, route: openai, capability: basic, streaming: nonstream, assertions: [works, cost_logged], source: "response_api_endpoints/endpoints.py:26", rationale: "Cost logged on responses"}
- {id: llm.responses.openai.tool_use.nonstream.works, module: llm, tier: P0, subject_endpoint: responses, route: openai, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Tool calls via Responses API"}
- {id: llm.responses.openai.vision.nonstream.works, module: llm, tier: P0, subject_endpoint: responses, route: openai, capability: vision, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Vision via Responses API"}
- {id: llm.responses.anthropic.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: anthropic, capability: basic, streaming: nonstream, assertions: [works], source: "response_api_endpoints/endpoints.py:26", rationale: "Responses w/ Anthropic translation (smoke)"}
- {id: llm.responses.anthropic.tool_use.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: anthropic, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Responses tool calls w/ Anthropic"}
- {id: llm.responses.bedrock_converse.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "response_api_endpoints/endpoints.py:26", rationale: "Responses w/ Bedrock Converse (smoke)"}
- {id: llm.responses.bedrock_converse.tool_use.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: bedrock_converse, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Responses tool calls w/ Converse"}
- {id: llm.responses.vertex.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "response_api_endpoints/endpoints.py:26", rationale: "Responses w/ Vertex (smoke)"}
- {id: llm.responses.vertex.tool_use.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: vertex, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Responses tool calls w/ Vertex"}
- {id: llm.responses.azure_openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "response_api_endpoints/endpoints.py:26", rationale: "Responses w/ Azure OpenAI (smoke)"}
- {id: llm.responses.azure_openai.tool_use.nonstream.works, module: llm, tier: P1, subject_endpoint: responses, route: azure_openai, capability: tool_use, streaming: nonstream, assertions: [works], source: "model_prices json", rationale: "Responses tool calls w/ Azure OpenAI"}

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# LLM non-conversational endpoints. Grounded in litellm/proxy endpoints + llms/ handlers.
- {id: llm.embeddings.openai.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: embeddings, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_embeddings_endpoint_e2e.py:23", rationale: "Core endpoint, live vector response"}
- {id: llm.embeddings.openai.basic.nonstream.cost_logged, module: llm, tier: P0, subject_endpoint: embeddings, route: openai, capability: basic, streaming: nonstream, assertions: [cost_logged], source: "SPEND_TRACKING_COVERAGE_MATRIX.md:34", rationale: "Cost tracking on embeddings"}
- {id: llm.embeddings.azure_openai.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: embeddings, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "llms/azure/azure.py", rationale: "Azure embeddings via translation"}
- {id: llm.embeddings.bedrock.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: embeddings, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "llms/bedrock/embed/embedding.py", rationale: "Bedrock Titan embeddings"}
- {id: llm.embeddings.vertex.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: embeddings, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "vertex_embeddings/embedding_handler.py", rationale: "Vertex embeddings"}
- {id: llm.embeddings.cohere.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: embeddings, route: cohere, capability: basic, streaming: nonstream, assertions: [works], source: "llms/cohere/embed/handler.py", rationale: "Cohere embeddings"}
- {id: llm.embeddings.anthropic.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: embeddings, route: anthropic, capability: basic, streaming: nonstream, assertions: [works], source: "llms/anthropic/chat/handler.py", rationale: "Anthropic vector API (verify support)"}
- {id: llm.batches.openai.create.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Core batch create"}
- {id: llm.batches.openai.retrieve.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Batch retrieve, id round-trip + status"}
- {id: llm.batches.openai.cancel.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Batch cancel"}
- {id: llm.batches.openai.list.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Batch list envelope"}
- {id: llm.batches.openai.file_lifecycle.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "File upload/retrieve/delete for batch flow"}
- {id: llm.batches.openai_encoded.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py", rationale: "Encoded scenario lifecycle"}
- {id: llm.batches.openai_unified.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py", rationale: "Unified/managed-id scenario"}
- {id: llm.batches.openai_model_param.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py", rationale: "Model-param scenario"}
- {id: llm.batches.openai_provider_fallback.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py", rationale: "Provider-fallback raw-id scenario"}
- {id: llm.batches.azure_openai.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:98", rationale: "Azure batches all scenarios"}
- {id: llm.batches.vertex.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:98", rationale: "Vertex batches"}
- {id: llm.batches.bedrock.basic.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:98", rationale: "Bedrock batches (encoded/unified only)"}
- {id: llm.batches.openai.key_model_access_denied.nonstream.works, module: llm, tier: P0, subject_endpoint: batches, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_batches_e2e.py", rationale: "Key model restriction 403 on upload/create"}
- {id: llm.files.openai.upload.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "openai_files_endpoints/files_endpoints.py:46", rationale: "File upload returns OpenAIFileObject"}
- {id: llm.files.openai.retrieve.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "files_endpoints.py", rationale: "File retrieve by id"}
- {id: llm.files.openai.delete.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "files_endpoints.py", rationale: "File delete returns deleted=true"}
- {id: llm.files.openai.list.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "files_endpoints.py", rationale: "File list paginated"}
- {id: llm.files.azure_openai.upload.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:45", rationale: "Azure file upload managed backend"}
- {id: llm.files.vertex.upload.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:52", rationale: "Vertex file upload to GCS"}
- {id: llm.files.bedrock.upload.nonstream.works, module: llm, tier: P0, subject_endpoint: files, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "batches/capabilities.py:59", rationale: "Bedrock file upload to S3"}
- {id: llm.rerank.cohere.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: rerank, route: cohere, capability: basic, streaming: nonstream, assertions: [works], source: "test_rerank_e2e.py:29", rationale: "Cohere rerank, top_n + relevance_score"}
- {id: llm.rerank.bedrock.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: rerank, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "llms/bedrock/rerank/handler.py", rationale: "Bedrock rerank"}
- {id: llm.rerank.together_ai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: rerank, route: together_ai, capability: basic, streaming: nonstream, assertions: [works], source: "llms/together_ai/rerank/handler.py", rationale: "Together rerank"}
- {id: llm.images_generations.openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: images_generations, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_image_generation_e2e.py:22", rationale: "OpenAI image gen, b64/url"}
- {id: llm.images_generations.azure_openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: images_generations, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "llms/azure/azure.py", rationale: "Azure DALL-E"}
- {id: llm.images_generations.vertex.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: images_generations, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "vertex_ai/image_generation/image_generation_handler.py", rationale: "Vertex Imagen"}
- {id: llm.images_generations.bedrock.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: images_generations, route: bedrock_converse, capability: basic, streaming: nonstream, assertions: [works], source: "bedrock/image_generation/image_handler.py", rationale: "Bedrock Titan Image"}
- {id: llm.images_generations.black_forest_labs.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: images_generations, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "black_forest_labs/image_generation/handler.py", rationale: "BFL Flux via OpenAI-compat"}
- {id: llm.audio_speech.openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_speech, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "test_audio_speech_e2e.py:22", rationale: "OpenAI TTS binary audio"}
- {id: llm.audio_speech.openai.basic.stream.works, module: llm, tier: P1, subject_endpoint: audio_speech, route: openai, capability: basic, streaming: stream, assertions: [works], source: "proxy_server.py:9043", rationale: "TTS streaming chunk generator"}
- {id: llm.audio_speech.azure_openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_speech, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "llms/azure/azure.py", rationale: "Azure TTS"}
- {id: llm.audio_speech.vertex.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_speech, route: vertex, capability: basic, streaming: nonstream, assertions: [works], source: "vertex_ai/text_to_speech/text_to_speech_handler.py", rationale: "Vertex TTS"}
- {id: llm.audio_transcriptions.openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_transcriptions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "openai/transcriptions/handler.py", rationale: "OpenAI Whisper"}
- {id: llm.audio_transcriptions.azure_openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: audio_transcriptions, route: azure_openai, capability: basic, streaming: nonstream, assertions: [works], source: "azure/audio_transcriptions.py", rationale: "Azure STT"}
- {id: llm.audio_transcriptions.soniox.basic.nonstream.works, module: llm, tier: P2, subject_endpoint: audio_transcriptions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "soniox/audio_transcription/handler.py", rationale: "Soniox via OpenAI-compat (smoke)"}
- {id: llm.audio_transcriptions.nvidia_riva.basic.nonstream.works, module: llm, tier: P2, subject_endpoint: audio_transcriptions, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "nvidia_riva/audio_transcription/handler.py", rationale: "NVIDIA Riva (smoke)"}
- {id: llm.moderations.openai.basic.nonstream.works, module: llm, tier: P1, subject_endpoint: moderations, route: openai, capability: basic, streaming: nonstream, assertions: [works], source: "proxy_server.py", rationale: "OpenAI moderations (only provider)"}

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# Logging integration delivery (behavior features). Grounded in litellm/integrations/.
- {id: logging.langfuse.success.logs_spend, module: logging, tier: P0, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages, embeddings], source: "integrations/langfuse/langfuse.py", rationale: "Primary tracing backend; cost accuracy"}
- {id: logging.langfuse.failure.logs_spend, module: logging, tier: P0, event: failure, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langfuse/langfuse.py", rationale: "Failure path must still track spend"}
- {id: logging.langfuse.stream.logs_spend, module: logging, tier: P0, event: stream, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langfuse/langfuse.py", rationale: "Streaming token counts aggregate"}
- {id: logging.s3.success.writes_object, module: logging, tier: P0, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages, embeddings], source: "integrations/s3_v2.py", rationale: "Primary audit trail; batch flush no-drop"}
- {id: logging.s3.failure.writes_object, module: logging, tier: P0, event: failure, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/s3_v2.py", rationale: "Failed calls persisted for compliance"}
- {id: logging.gcs_bucket.success.writes_object, module: logging, tier: P0, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages, embeddings], source: "integrations/gcs_bucket/gcs_bucket.py", rationale: "GCS parallel to S3"}
- {id: logging.datadog.success.exports_metric, module: logging, tier: P0, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/datadog/datadog.py", rationale: "Powers dashboards/alerts; cardinality regressions common"}
- {id: logging.datadog.failure.exports_metric, module: logging, tier: P0, event: failure, assertions: [exports_metric], exercised_on: [chat_completions], source: "integrations/datadog/datadog.py", rationale: "Failure metrics for alerting/SLO"}
- {id: logging.prometheus.success.exports_metric, module: logging, tier: P0, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/prometheus.py", rationale: "Standard OSS metrics; per-key cardinality (existing e2e)"}
- {id: logging.otel.success.exports_metric, module: logging, tier: P0, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/otel/logger.py", rationale: "OTEL spans on every call path"}
- {id: logging.otel.failure.exports_metric, module: logging, tier: P0, event: failure, assertions: [exports_metric], exercised_on: [chat_completions, messages], source: "integrations/otel/logger.py", rationale: "Error spans for observability continuity"}
- {id: logging.braintrust.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/braintrust_logging.py", rationale: "Evals platform spend"}
- {id: logging.langsmith.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langsmith.py", rationale: "LangChain ecosystem"}
- {id: logging.arize.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, embeddings], source: "integrations/arize/arize.py", rationale: "ML-ops observability"}
- {id: logging.mlflow.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/mlflow.py", rationale: "Experiment tracking cost/run"}
- {id: logging.opik.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/opik/opik.py", rationale: "Eval platform spend/case"}
- {id: logging.openmeter.success.exports_metric, module: logging, tier: P1, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/openmeter.py", rationale: "Usage metering for billing"}
- {id: logging.literal_ai.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/literal_ai.py", rationale: "Tracing platform spend"}
- {id: logging.posthog.success.exports_metric, module: logging, tier: P1, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages], source: "integrations/posthog.py", rationale: "Product analytics batching"}
- {id: logging.azure_storage.success.writes_object, module: logging, tier: P1, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/azure_storage/azure_storage.py", rationale: "Azure blob for enterprise"}
- {id: logging.cloudzero.success.logs_spend, module: logging, tier: P1, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/cloudzero/cloudzero.py", rationale: "Cost ops correlation"}
- {id: logging.focus.success.writes_object, module: logging, tier: P1, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/focus/focus_logger.py", rationale: "Cost mgmt multi-destination export"}
- {id: logging.niche_integrations.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE cohort: athina/galileo/deepeval/langtrace/weave/lunary/humanloop/traceloop/helicone/argilla/newrelic/sqs/supabase/dynamodb/agentops/lago/etc"}
- {id: logging.niche_integrations.failure.logs_spend, module: logging, tier: P2, event: failure, assertions: [logs_spend], exercised_on: [chat_completions], source: grammar, rationale: "SMOKE niche failure path"}

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# MCP module. Grounded in litellm/proxy/_experimental/mcp_server/. See tests/e2e/CLAUDE.md for the grammar.
- id: mcp.list_tools.api_key.succeeds
module: mcp
tier: P0
operation: list_tools
auth_family: api_key
assertions: [succeeds]
source: "server.py:637"
rationale: Core operation; most common auth path; high usage
- id: mcp.list_tools.api_key.denied_without_permission
module: mcp
tier: P0
operation: list_tools
auth_family: api_key
assertions: [denied_without_permission]
source: "mcp_server_manager.py:1409"
rationale: Permission guard is high blast-radius; multi-tenant safety
- id: mcp.call_tool.api_key.succeeds
module: mcp
tier: P0
operation: call_tool
auth_family: api_key
assertions: [succeeds]
source: "server.py:849"
rationale: Primary operation; customer-critical; high usage
- id: mcp.call_tool.api_key.denied_without_permission
module: mcp
tier: P0
operation: call_tool
auth_family: api_key
assertions: [denied_without_permission]
source: "rest_endpoints.py:305-386"
rationale: Tool-level permission guard; multi-tenant safety
- id: mcp.list_tools.bearer.succeeds
module: mcp
tier: P1
operation: list_tools
auth_family: bearer
assertions: [succeeds]
source: "server.py:662"
rationale: OAuth/bearer token flow; upstream delegation
- id: mcp.call_tool.bearer.succeeds
module: mcp
tier: P1
operation: call_tool
auth_family: bearer
assertions: [succeeds]
source: "server.py:886"
rationale: Bearer token forwarding for tool invocation
- id: mcp.list_tools.oauth.succeeds
module: mcp
tier: P1
operation: list_tools
auth_family: oauth
assertions: [succeeds]
source: "rest_endpoints.py:138-188"
rationale: Interactive OAuth2 flow; live token management
- id: mcp.call_tool.oauth.succeeds
module: mcp
tier: P1
operation: call_tool
auth_family: oauth
assertions: [succeeds]
source: "db.py user_oauth_credential lookup"
rationale: OAuth2 token passthrough; per-user credential storage
- id: mcp.list_tools.none.succeeds
module: mcp
tier: P1
operation: list_tools
auth_family: none
assertions: [succeeds]
source: "mcp_server_manager.py:1485-1492"
rationale: Public/anonymous servers; delegate_auth_to_upstream
- id: mcp.call_tool.none.succeeds
module: mcp
tier: P1
operation: call_tool
auth_family: none
assertions: [succeeds]
source: "rest_endpoints.py:305-334"
rationale: No upstream auth required; demo servers
- id: mcp.get_prompt.api_key.succeeds
module: mcp
tier: P1
operation: get_prompt
auth_family: api_key
assertions: [succeeds]
source: "server.py:1042"
rationale: Prompt op; same auth stack as tools
- id: mcp.read_resource.api_key.succeeds
module: mcp
tier: P1
operation: read_resource
auth_family: api_key
assertions: [succeeds]
source: "server.py:1177"
rationale: Resource op; same permission model as tools
- id: mcp.list_prompts.api_key.succeeds
module: mcp
tier: P2
operation: list_prompts
auth_family: api_key
assertions: [succeeds]
source: "server.py:993"
rationale: Smoke-level; same auth stack as list_tools
- id: mcp.list_resources.api_key.succeeds
module: mcp
tier: P2
operation: list_resources
auth_family: api_key
assertions: [succeeds]
source: "server.py:1089"
rationale: Smoke; rarely used; same auth model as tools

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# Management/UI endpoint features. Grounded in litellm/proxy/management_endpoints/.
- {id: mgmt.key.generate.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "key_management_endpoints.py:1444", rationale: "API key survives DB roundtrip"}
- {id: mgmt.key.generate.admin_only, module: mgmt, tier: P0, surface: api, assertions: [admin_only], source: "key_management_endpoints.py:1444", rationale: "Only master/team-admin creates keys"}
- {id: mgmt.key.generate.happy_path, module: mgmt, tier: P0, surface: ui, assertions: [happy_path], source: "ui_sso.py:420", rationale: "SSO-driven key gen (UI path)"}
- {id: mgmt.key.update.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "key_management_endpoints.py:2462", rationale: "Budget/model changes persist"}
- {id: mgmt.key.update.admin_only, module: mgmt, tier: P0, surface: api, assertions: [admin_only], source: "key_management_endpoints.py:2462", rationale: "Non-admin cannot escalate perms"}
- {id: mgmt.key.delete.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "key_management_endpoints.py:3122", rationale: "Deletion revokes future calls"}
- {id: mgmt.key.delete.admin_only, module: mgmt, tier: P0, surface: api, assertions: [admin_only], source: "key_management_endpoints.py:3122", rationale: "Non-owner cannot delete"}
- {id: mgmt.key.info.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "key_management_endpoints.py:3380", rationale: "Info reflects all writes"}
- {id: mgmt.team.new.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "team_endpoints.py:897", rationale: "team_id/alias/budgets stored"}
- {id: mgmt.team.new.admin_only, module: mgmt, tier: P0, surface: api, assertions: [admin_only], source: "team_endpoints.py:897", rationale: "Only org-admin/master creates teams"}
- {id: mgmt.team.member_add.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "team_endpoints.py:2424", rationale: "Membership + per-member budget persist"}
- {id: mgmt.team.member_add.member_forbidden, module: mgmt, tier: P0, surface: api, assertions: [member_forbidden], source: "team_endpoints.py:2424", rationale: "Non-admin forbidden to add"}
- {id: mgmt.team.member_delete.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "team_endpoints.py:2800", rationale: "Removal revokes team key access"}
- {id: mgmt.team.member_delete.member_forbidden, module: mgmt, tier: P0, surface: api, assertions: [member_forbidden], source: "team_endpoints.py:2800", rationale: "Non-admin forbidden to remove"}
- {id: mgmt.budget.new.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "budget_management_endpoints.py:40", rationale: "max/soft/reset windows persist"}
- {id: mgmt.budget.new.admin_only, module: mgmt, tier: P0, surface: api, assertions: [admin_only], source: "budget_management_endpoints.py:40", rationale: "Requires master/admin"}
- {id: mgmt.model.add.persists, module: mgmt, tier: P0, surface: api, assertions: [persists], source: "model_management_endpoints.py:1201", rationale: "Registration persists for routing"}
- {id: mgmt.model.add.admin_only, module: mgmt, tier: P0, surface: api, assertions: [admin_only], source: "model_management_endpoints.py:1201", rationale: "Non-admin cannot inject model config"}
- {id: mgmt.user.new.happy_path, module: mgmt, tier: P0, surface: api, assertions: [happy_path], source: "internal_user_endpoints.py:360", rationale: "User creation full cycle"}
- {id: mgmt.key.list.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "key_management_endpoints.py:5119", rationale: "Key inventory pagination"}
- {id: mgmt.key.block.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "key_management_endpoints.py:5849", rationale: "Blocked stays blocked on restart"}
- {id: mgmt.key.unblock.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "key_management_endpoints.py:5960", rationale: "Unblock restores access"}
- {id: mgmt.key.regenerate.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "key_management_endpoints.py:6071", rationale: "Rotation: new works, old invalid"}
- {id: mgmt.key.health.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "key_management_endpoints.py:4292", rationale: "Key health endpoint"}
- {id: mgmt.key.bulk_update.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "key_management_endpoints.py:2677", rationale: "Batch key updates"}
- {id: mgmt.team.update.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "team_endpoints.py:1582", rationale: "Metadata/budget updates persist"}
- {id: mgmt.team.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "team_endpoints.py:1750", rationale: "Deletion prevents key access"}
- {id: mgmt.team.block.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "team_endpoints.py", rationale: "Block suspends all members"}
- {id: mgmt.team.info.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "team_endpoints.py:2244", rationale: "Metadata+members+budgets"}
- {id: mgmt.team.list.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "team_endpoints.py:3645", rationale: "Pagination/filtering"}
- {id: mgmt.team.member_update.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "team_endpoints.py:2768", rationale: "Member budget/role updates persist"}
- {id: mgmt.user.update.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "internal_user_endpoints.py:555", rationale: "Metadata/perm updates persist"}
- {id: mgmt.user.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "internal_user_endpoints.py:640", rationale: "Deletion revokes keys+teams"}
- {id: mgmt.user.list.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "internal_user_endpoints.py:475", rationale: "Admin view all users"}
- {id: mgmt.user.info.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "internal_user_endpoints.py:440", rationale: "Roles/perms/team membership"}
- {id: mgmt.organization.new.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "organization_endpoints.py:403", rationale: "Org for multi-tenant isolation"}
- {id: mgmt.organization.update.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "organization_endpoints.py:545", rationale: "Org metadata updates persist"}
- {id: mgmt.organization.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "organization_endpoints.py:710", rationale: "Cascades to teams/keys"}
- {id: mgmt.organization.member_add.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "organization_endpoints.py:835", rationale: "Org member onboarding"}
- {id: mgmt.customer.new.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "customer_endpoints.py:372", rationale: "End-user for spend tracking"}
- {id: mgmt.customer.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "customer_endpoints.py:480", rationale: "Removes from spend tracking"}
- {id: mgmt.end_user.new.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "customer_endpoints.py:730", rationale: "End-user create (synonym)"}
- {id: mgmt.tag.new.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "tag_management_endpoints.py:160", rationale: "Tag for spend categorization"}
- {id: mgmt.tag.list.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "tag_management_endpoints.py:315", rationale: "Tag enumeration"}
- {id: mgmt.tag.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "tag_management_endpoints.py:390", rationale: "Stops future tagging"}
- {id: mgmt.model.update.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "model_management_endpoints.py:1358", rationale: "Pricing/concurrency persist"}
- {id: mgmt.model.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "model_management_endpoints.py:1045", rationale: "Removes from registry"}
- {id: mgmt.model.block.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "model_management_endpoints.py", rationale: "Blocked model stays blocked"}
- {id: mgmt.access_group.new.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "model_access_group_management_endpoints.py:450", rationale: "Model permissioning group"}
- {id: mgmt.access_group.info.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "model_access_group_management_endpoints.py:600", rationale: "Access group membership query"}
- {id: mgmt.mcp_server.register.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "mcp_management_endpoints.py:880", rationale: "MCP server registration"}
- {id: mgmt.mcp_server.approve.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "mcp_management_endpoints.py:1200", rationale: "Admin approval persists"}
- {id: mgmt.budget.update.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "budget_management_endpoints.py:155", rationale: "Limit changes apply"}
- {id: mgmt.budget.delete.persists, module: mgmt, tier: P1, surface: api, assertions: [persists], source: "budget_management_endpoints.py:280", rationale: "Clears limits"}
- {id: mgmt.budget.list.happy_path, module: mgmt, tier: P1, surface: api, assertions: [happy_path], source: "budget_management_endpoints.py:215", rationale: "Budget enumeration"}
- {id: mgmt.callback.list.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "callback_management_endpoints.py", rationale: "Callback config (smoke)"}
- {id: mgmt.cache_settings.update.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "cache_settings_endpoints.py", rationale: "Cache config (smoke)"}
- {id: mgmt.cost_tracking.estimate.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "cost_tracking_settings.py", rationale: "Cost estimate (smoke)"}
- {id: mgmt.router_settings.update.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "router_settings_endpoints.py", rationale: "Router config (smoke)"}
- {id: mgmt.jwt_key_mapping.new.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "jwt_key_mapping_endpoints.py", rationale: "JWT->key mapping (smoke)"}
- {id: mgmt.compliance.gdpr.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "compliance_endpoints.py", rationale: "GDPR ops (smoke)"}
- {id: mgmt.tool_management.list.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "tool_management_endpoints.py", rationale: "Tool inventory (smoke)"}
- {id: mgmt.fallback_management.update.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "fallback_management_endpoints.py", rationale: "Fallback config (smoke)"}
- {id: mgmt.config_override.hashicorp_vault.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "config_override_endpoints.py", rationale: "Vault integration (smoke)"}
- {id: mgmt.workflow.list.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "workflow_management_endpoints.py", rationale: "Workflow tracking (smoke)"}
- {id: mgmt.credential_migration.check.happy_path, module: mgmt, tier: P2, surface: api, assertions: [happy_path], source: "key_management_endpoints.py:4252", rationale: "Encryption migration (smoke)"}

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# Other (holding pen). Grounded in litellm/proxy/auth/ + health_endpoints/ + proxy_server.py.
# PROMOTION NOTE: the auth cluster (~14 cells) is a candidate to promote to its own module once stable.
- {id: other.auth.master_key.valid_allows, module: other, tier: P0, area: auth, assertions: [valid_allows], source: "user_api_key_auth.py:1569-1588", rationale: "Master key authenticates; timing-safe compare"}
- {id: other.auth.master_key.invalid_denied, module: other, tier: P0, area: auth, assertions: [invalid_denied], source: "user_api_key_auth.py:1580", rationale: "Invalid master key rejected"}
- {id: other.auth.jwt.valid_token_allows, module: other, tier: P0, area: auth, assertions: [valid_token_allows], source: "handle_jwt.py:77-150", rationale: "Valid JWT with correct issuer + claims grants access"}
- {id: other.auth.jwt.expired_denied, module: other, tier: P0, area: auth, assertions: [expired_denied], source: "handle_jwt.py:125-135", rationale: "Expired JWT rejected even with valid signature"}
- {id: other.auth.jwt.invalid_signature_denied, module: other, tier: P0, area: auth, assertions: [invalid_signature_denied], source: "handle_jwt.py:145-150", rationale: "Bad/missing signature fails verification"}
- {id: other.auth.virtual_key.route_permission_enforced, module: other, tier: P0, area: auth, assertions: [route_permission_enforced], source: "route_checks.py:89-151", rationale: "allowed_routes whitelist denies disallowed routes"}
- {id: other.auth.virtual_key.route_group_allowed, module: other, tier: P1, area: auth, assertions: [route_group_allowed], source: "route_checks.py:106-128", rationale: "allowed_routes=[llm_api_routes] grants all LLM endpoints"}
- {id: other.auth.passthrough.model_allowlist_enforced, module: other, tier: P1, area: auth, assertions: [model_allowlist_enforced], source: "route_checks.py:135-151", rationale: "Passthrough enforces per-key model allow-lists"}
- {id: other.auth.oauth2.token_valid_allows, module: other, tier: P1, area: auth, assertions: [token_valid_allows], source: "oauth2_check.py:15-73", rationale: "OAuth2 introspection grants active token"}
- {id: other.auth.oauth2.token_invalid_denied, module: other, tier: P1, area: auth, assertions: [token_invalid_denied], source: "oauth2_check.py:37-73", rationale: "Expired/inactive OAuth2 token denied"}
- {id: other.auth.ip_allowlist.internal_ip_allows, module: other, tier: P1, area: auth, assertions: [internal_ip_allows], source: "ip_address_utils.py:54-76", rationale: "Internal CIDR bypasses public-API restriction"}
- {id: other.auth.ip_allowlist.external_ip_denied_to_private, module: other, tier: P1, area: auth, assertions: [external_ip_denied_to_private], source: "ip_address_utils.py:54-76", rationale: "External IP cannot reach internal-only resources"}
- {id: other.lifecycle.readiness.public_probe, module: other, tier: P0, area: lifecycle, assertions: [public_probe], source: "_health_endpoints.py:1551-1570", rationale: "Unauthenticated /health/readiness safe for LBs"}
- {id: other.lifecycle.readiness.reports_db_status, module: other, tier: P0, area: lifecycle, assertions: [reports_db_status], source: "_health_endpoints.py:1551-1570", rationale: "readiness distinguishes healthy vs DB-unreachable"}
- {id: other.lifecycle.readiness.shutting_down_returns_503, module: other, tier: P0, area: lifecycle, assertions: [shutting_down_returns_503], source: "_health_endpoints.py:1554-1556", rationale: "Graceful shutdown drains LB via 503"}
- {id: other.lifecycle.readiness_details.authenticated_diagnostics, module: other, tier: P1, area: lifecycle, assertions: [authenticated_diagnostics], source: "_health_endpoints.py:1574-1584", rationale: "Auth'd details expose cache/callback status"}
- {id: other.lifecycle.liveness.ping, module: other, tier: P1, area: lifecycle, assertions: [ping], source: "_health_endpoints.py:134-155", rationale: "Liveness confirms server responding"}
- {id: other.lifecycle.startup.config_loads, module: other, tier: P0, area: lifecycle, assertions: [config_loads], source: "proxy_server.py:4020-4100", rationale: "Startup loads YAML, resolves env, persists to DB"}
- {id: other.lifecycle.startup.env_vars_resolved, module: other, tier: P1, area: lifecycle, assertions: [env_vars_resolved], source: "proxy_server.py:3984-4010", rationale: "os.environ/ refs resolved at startup"}
- {id: other.lifecycle.background_health_check.interval_configurable, module: other, tier: P1, area: lifecycle, assertions: [interval_configurable], source: "proxy_server.py:3245-3310", rationale: "Background checks run at configurable interval"}
- {id: other.config.runtime_update.applies_at_runtime, module: other, tier: P0, area: config, assertions: [applies_at_runtime], source: "proxy_server.py:14014-14060", rationale: "/config/update persists to DB + invalidates cache"}
- {id: other.config.general_settings.alert_webhook_side_effect, module: other, tier: P1, area: config, assertions: [alert_webhook_side_effect], source: "proxy_server.py:14215", rationale: "alert_to_webhook_url auto-enables slack alerting"}
- {id: other.config.secret_resolution.kms_integration, module: other, tier: P1, area: config, assertions: [kms_integration], source: "proxy_server.py:3984-4010", rationale: "Resolves secrets from Vault/KMS at startup"}
- {id: other.config.overrides.audit_logged, module: other, tier: P1, area: config, assertions: [audit_logged], source: "config_override_endpoints.py:67-100", rationale: "Config override mutations audit-logged, values redacted"}
- {id: other.key_mgmt.regenerate.grace_period_honored, module: other, tier: P1, area: auth, assertions: [grace_period_honored], source: "key_management_endpoints.py:4503-4560", rationale: "Old key valid during grace_period then revoked"}
- {id: other.key_mgmt.spend_reset.resets_to_value, module: other, tier: P1, area: auth, assertions: [resets_to_value], source: "key_management_endpoints.py:4841", rationale: "reset_spend resets accumulated spend"}

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@ -0,0 +1,26 @@
"""Load and validate the registry: the denominator, built in one shot from the YAMLs."""
from __future__ import annotations
from collections import Counter
from pathlib import Path
import yaml
from .schema import CELL_ADAPTER, Cell
REGISTRY_DIR = Path(__file__).resolve().parent
def load_registry(registry_dir: Path = REGISTRY_DIR) -> tuple[Cell, ...]:
"""Every cell across every `*.yaml`, validated. Raises on a schema violation or
a duplicate id, since either would corrupt the coverage denominator."""
cells = tuple(
CELL_ADAPTER.validate_python(row)
for path in sorted(registry_dir.glob("*.yaml"))
for row in (yaml.safe_load(path.read_text()) or ())
)
duplicates = sorted(cid for cid, n in Counter(c.id for c in cells).items() if n > 1)
if duplicates:
raise ValueError(f"duplicate cell ids in registry: {duplicates}")
return cells

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# Reliability & Performance (behavior features). Grounded in litellm/router.py + router_strategy/ + router_utils/.
- {id: reliability.fallback.5xx.routes_to_fallback, module: reliability, tier: P0, behavior: fallback, variant: "5xx", assertions: [routes_to_fallback], exercised_on: [chat_completions, messages], source: "litellm/router.py:2024", rationale: "Reroute on provider 5xx to alternate deployment"}
- {id: reliability.fallback.context_window.routes_to_fallback, module: reliability, tier: P0, behavior: fallback, variant: context_window, assertions: [routes_to_fallback], exercised_on: [chat_completions, messages], source: "litellm/router.py:6108", rationale: "Fallback when model exceeds context limit"}
- {id: reliability.fallback.content_policy.routes_to_fallback, module: reliability, tier: P0, behavior: fallback, variant: content_policy, assertions: [routes_to_fallback], exercised_on: [chat_completions, messages], source: "litellm/router.py:6023", rationale: "Reroute on content-policy violation"}
- {id: reliability.fallback.timeout.routes_to_fallback, module: reliability, tier: P0, behavior: fallback, variant: "timeout", assertions: [routes_to_fallback], exercised_on: [chat_completions, messages], source: "litellm/router.py:2766", rationale: "Fallback on request timeout"}
- {id: reliability.retry.5xx.succeeds_within_retries, module: reliability, tier: P0, behavior: retry, variant: "5xx", assertions: [succeeds_within_retries], exercised_on: [chat_completions, messages], source: "litellm/router.py:6414", rationale: "Transient 5xx often succeeds on retry"}
- {id: reliability.retry.timeout.succeeds_within_retries, module: reliability, tier: P0, behavior: retry, variant: timeout, assertions: [succeeds_within_retries], exercised_on: [chat_completions, messages], source: "get_retry_from_policy.py:44", rationale: "Timeout retried per policy"}
- {id: reliability.retry.429.succeeds_within_retries, module: reliability, tier: P0, behavior: retry, variant: "429", assertions: [succeeds_within_retries], exercised_on: [chat_completions, messages], source: "get_retry_from_policy.py:46", rationale: "429 retried per RateLimitErrorRetries policy"}
- {id: reliability.retry.auth.succeeds_within_retries, module: reliability, tier: P1, behavior: retry, variant: auth, assertions: [succeeds_within_retries], exercised_on: [chat_completions, messages], source: "get_retry_from_policy.py:42", rationale: "Transient auth glitch retry"}
- {id: reliability.retry.context_window.succeeds_within_retries, module: reliability, tier: P1, behavior: retry, variant: context_window, assertions: [succeeds_within_retries], exercised_on: [chat_completions, messages], source: "get_retry_from_policy.py:51", rationale: "Multi-attempt on context error"}
- {id: reliability.cooldown.5xx.trips_then_recovers, module: reliability, tier: P0, behavior: cooldown, variant: "5xx", assertions: [trips_then_recovers], exercised_on: [chat_completions, messages], source: "cooldown_handlers.py:40", rationale: "Deployment cools after repeated 5xx, recovers after cooldown_time"}
- {id: reliability.cooldown.429.trips_then_recovers, module: reliability, tier: P0, behavior: cooldown, variant: "429", assertions: [trips_then_recovers], exercised_on: [chat_completions, messages], source: "cooldown_handlers.py:69", rationale: "Cools on 429, avoids hammering exhausted provider"}
- {id: reliability.cooldown.auth.trips_then_recovers, module: reliability, tier: P1, behavior: cooldown, variant: auth, assertions: [trips_then_recovers], exercised_on: [chat_completions, messages], source: "cooldown_handlers.py:74", rationale: "Cools on 401 auth error"}
- {id: reliability.cooldown.timeout.trips_then_recovers, module: reliability, tier: P1, behavior: cooldown, variant: timeout, assertions: [trips_then_recovers], exercised_on: [chat_completions, messages], source: "cooldown_handlers.py:77", rationale: "Cools on 408 timeout"}
- {id: reliability.ratelimit.rpm.blocks_over_limit, module: reliability, tier: P0, behavior: ratelimit, variant: rpm, assertions: [blocks_over_limit], exercised_on: [chat_completions, messages], source: "dynamic_rate_limiter_v3.py", rationale: "v3 limiter enforces RPM per key/team/model; 429 on breach"}
- {id: reliability.ratelimit.tpm.blocks_over_limit, module: reliability, tier: P0, behavior: ratelimit, variant: tpm, assertions: [blocks_over_limit], exercised_on: [chat_completions, messages], source: "dynamic_rate_limiter_v3.py", rationale: "v3 limiter enforces TPM per key/team/model; 429 on breach"}
- {id: reliability.ratelimit.priority_generous.picks_under_tpm, module: reliability, tier: P1, behavior: ratelimit, variant: priority_generous, assertions: [picks_under_tpm], exercised_on: [chat_completions, messages], source: "dynamic_rate_limiter_v3.py:36-52", rationale: "Generous mode (<80% sat) allows priority borrowing"}
- {id: reliability.ratelimit.priority_strict.picks_under_tpm, module: reliability, tier: P1, behavior: ratelimit, variant: priority_strict, assertions: [picks_under_tpm], exercised_on: [chat_completions, messages], source: "dynamic_rate_limiter_v3.py:53-71", rationale: "Strict mode (>=80% sat) enforces priority fairness"}
- {id: reliability.routing.simple_shuffle.picks_healthy_deployment, module: reliability, tier: P1, behavior: routing, variant: simple_shuffle, assertions: [picks_healthy_deployment], exercised_on: [chat_completions, messages], source: "router_strategy/simple_shuffle.py", rationale: "Baseline weighted/uniform pick"}
- {id: reliability.routing.latency_based.picks_lowest_latency, module: reliability, tier: P1, behavior: routing, variant: latency_based, assertions: [picks_lowest_latency], exercised_on: [chat_completions, messages], source: "router_strategy/lowest_latency.py", rationale: "Routes to lowest-latency deployment"}
- {id: reliability.routing.cost_based.picks_lowest_cost, module: reliability, tier: P1, behavior: routing, variant: cost_based, assertions: [picks_lowest_cost], exercised_on: [chat_completions, messages], source: "router_strategy/lowest_cost.py", rationale: "Spend-aware routing"}
- {id: reliability.routing.usage_based.picks_under_tpm, module: reliability, tier: P0, behavior: routing, variant: usage_based, assertions: [picks_under_tpm], exercised_on: [chat_completions, messages], source: "router_strategy/lowest_tpm_rpm_v2.py", rationale: "Routes to lowest-TPM deployment; prevents over-allocation"}
- {id: reliability.routing.least_busy.picks_lowest_traffic, module: reliability, tier: P1, behavior: routing, variant: least_busy, assertions: [picks_lowest_traffic], exercised_on: [chat_completions, messages], source: "router_strategy/least_busy.py", rationale: "Fewest in-flight requests"}
- {id: reliability.cache.exact.returns_cached, module: reliability, tier: P1, behavior: cache, variant: exact, assertions: [returns_cached], exercised_on: [chat_completions, messages, embeddings], source: "litellm/caching/caching.py", rationale: "Response cache returns cached on exact match"}
- {id: reliability.cache.prompt_caching_model_select.returns_cached, module: reliability, tier: P1, behavior: cache, variant: prompt_caching_model_select, assertions: [returns_cached], exercised_on: [chat_completions], source: "router_utils/prompt_caching_cache.py", rationale: "Selects model supporting prompt caching for cacheable prefix"}
- {id: reliability.circuit_breaker.redis.trips_then_recovers, module: reliability, tier: P0, behavior: circuit_breaker, variant: redis, assertions: [trips_then_recovers], exercised_on: [chat_completions, messages, embeddings], source: "litellm/caching/redis_cache.py:99", rationale: "Redis breaker CLOSED->OPEN->HALF_OPEN; guards all cache/rate-limit ops"}
- {id: reliability.timeout.request_timeout.exceeds_deadline, module: reliability, tier: P1, behavior: timeout, variant: request_timeout, assertions: [exceeds_deadline], exercised_on: [chat_completions, messages], source: "litellm/router.py:545-551", rationale: "Per-request timeout raises Timeout"}
- {id: reliability.timeout.stream_timeout.exceeds_deadline, module: reliability, tier: P1, behavior: timeout, variant: stream_timeout, assertions: [exceeds_deadline], exercised_on: [chat_completions], source: "litellm/router.py:551", rationale: "Streaming chunk-delivery timeout"}
- {id: reliability.perf.latency.under_slo, module: reliability, tier: P1, behavior: perf, variant: latency, assertions: [under_slo], exercised_on: [chat_completions, messages], source: "router_strategy/lowest_latency.py", rationale: "Latency SLO (p50/p99) compliance"}
- {id: reliability.perf.throughput.under_slo, module: reliability, tier: P1, behavior: perf, variant: throughput, assertions: [under_slo], exercised_on: [chat_completions, messages], source: grammar, rationale: "Throughput SLO under load"}

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"""Registry row schema: the contract every denominator cell validates against.
A cell is one customer-noticeable behavior a single e2e test can assert pass/fail
on. `module` is the id's segment-1 prefix (seven of them); the six-way dashboard
rollup merges logging + guardrail via ROLLUP. The union is discriminated on
`module`, so an LLM row cannot carry a guardrail field and vice versa.
"""
from __future__ import annotations
from enum import Enum
from typing import Annotated, Literal
from pydantic import BaseModel, ConfigDict, Field, TypeAdapter
class Tier(str, Enum):
P0 = "P0"
P1 = "P1"
P2 = "P2"
class FailBeforeFix(str, Enum):
proven = "proven"
unproven = "unproven"
class _Base(BaseModel):
model_config = ConfigDict(frozen=True, extra="forbid")
id: str
tier: Tier
assertions: tuple[str, ...]
source: str
rationale: str = ""
fail_before_fix: FailBeforeFix = FailBeforeFix.unproven
supported: bool = True
class LlmCell(_Base):
module: Literal["llm"]
subject_endpoint: str
route: str
capability: str
streaming: Literal["stream", "nonstream", "na"]
class MgmtCell(_Base):
module: Literal["mgmt"]
surface: Literal["api", "ui"]
class McpCell(_Base):
module: Literal["mcp"]
operation: str
auth_family: Literal["none", "api_key", "bearer", "oauth"]
class ReliabilityCell(_Base):
module: Literal["reliability"]
behavior: str
variant: str
exercised_on: tuple[str, ...]
class LoggingCell(_Base):
module: Literal["logging"]
event: str
exercised_on: tuple[str, ...]
class GuardrailCell(_Base):
module: Literal["guardrail"]
hook_point: str
exercised_on: tuple[str, ...]
class OtherCell(_Base):
module: Literal["other"]
area: str
Cell = Annotated[
LlmCell | MgmtCell | McpCell | ReliabilityCell | LoggingCell | GuardrailCell | OtherCell,
Field(discriminator="module"),
]
CELL_ADAPTER: TypeAdapter[Cell] = TypeAdapter(Cell)
ROLLUP: dict[str, str] = {
"llm": "LLMs",
"mcp": "MCPs",
"mgmt": "Management/UI",
"reliability": "Reliability & Performance",
"logging": "Logging & Guardrails",
"guardrail": "Logging & Guardrails",
"other": "Other",
}
MODULE_ORDER: tuple[str, ...] = (
"LLMs",
"MCPs",
"Management/UI",
"Reliability & Performance",
"Logging & Guardrails",
"Other",
)

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"""Tests for the coverage-registry tooling: pure logic plus a registry canary.
No `e2e` marker, so these run without a proxy. They exercise the coverage math and
the registry loader, and guard the checked-in registry against schema drift and
duplicate ids.
"""
from __future__ import annotations
from pathlib import Path
import pytest
from coverage_registry.collector import compute_coverage
from coverage_registry.registry import load_registry
from coverage_registry.schema import GuardrailCell, LlmCell, LoggingCell, Tier
def _llm(cell_id: str, tier: Tier) -> LlmCell:
return LlmCell(
id=cell_id,
module="llm",
tier=tier,
assertions=("works",),
source="test",
subject_endpoint="chat_completions",
route="openai",
capability="basic",
streaming="nonstream",
)
def test_compute_coverage_counts_covered_p0_and_gaps() -> None:
cells = (_llm("llm.a", Tier.P0), _llm("llm.b", Tier.P0), _llm("llm.c", Tier.P1))
report = compute_coverage(cells, frozenset({"llm.a"}))
assert (report.total, report.covered) == (3, 1)
assert (report.p0_total, report.p0_covered) == (2, 1)
assert report.p0_gaps == ("llm.b",)
assert report.orphan_markers == ()
def test_orphan_marker_is_reported_not_counted() -> None:
cells = (_llm("llm.a", Tier.P0),)
report = compute_coverage(cells, frozenset({"llm.a", "llm.ghost"}))
assert report.covered == 1
assert report.orphan_markers == ("llm.ghost",)
def test_logging_and_guardrail_roll_up_into_one_module() -> None:
cells = (
LoggingCell(
id="logging.x",
module="logging",
tier=Tier.P0,
assertions=("logs_spend",),
source="t",
event="success",
exercised_on=("chat_completions",),
),
GuardrailCell(
id="guardrail.y",
module="guardrail",
tier=Tier.P1,
assertions=("blocks",),
source="t",
hook_point="pre_call",
exercised_on=("chat_completions",),
),
)
report = compute_coverage(cells, frozenset())
logging_and_guardrails = next(m for m in report.modules if m.module == "Logging & Guardrails")
assert logging_and_guardrails.total == 2
def test_real_registry_loads_and_ids_are_unique() -> None:
cells = load_registry()
ids = [c.id for c in cells]
assert len(cells) > 250
assert len(ids) == len(set(ids))
assert any(c.id == "logging.prometheus.success.exports_metric" for c in cells)
def test_load_registry_rejects_duplicate_ids(tmp_path: Path) -> None:
row = (
"- {id: llm.dup, module: llm, tier: P0, assertions: [works], source: t, "
"subject_endpoint: chat_completions, route: openai, capability: basic, streaming: nonstream}\n"
)
(tmp_path / "a.yaml").write_text(row)
(tmp_path / "b.yaml").write_text(row)
with pytest.raises(ValueError, match="duplicate cell ids"):
load_registry(tmp_path)