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test(e2e): retier coverage registry to the surfaces we commit to
Guardrails: keep bedrock, OpenAI moderations, the LiteLLM content filter and presidio at P0, promote llm_as_a_judge to P0, and drop the third-party vendor tail (lakera, ibm, semantic_guard, purview, pangea, headroom, generic api) to P2. AIM goes to P2 until its DRI lands a mock AIM server, since CI has no live AIM tenant. Logging: s3, GCS, prometheus, datadog and OTEL stay P0; the eval/analytics/cost destinations move to P2. Auth: virtual key and JWT are the committed paths, so route_group_allowed joins them at P0 and OAuth2 introspection plus the IP allowlist drop to P2. README records the policy: P0 + P1 is the number we drive to 95%, P2 rows stay enumerated so tail gaps remain visible without gating the target.
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Devin AI
parent
2f2e1e7519
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86e00c244c
4 changed files with 46 additions and 32 deletions
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@ -67,13 +67,27 @@ Strict mode exits non-zero on `@pytest.mark.covers(...)` ids that are not checke
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the registry. Add `--fail-on-collection-errors` when the job should also fail on pytest
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collection errors.
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## Tiering policy
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Tier is what we commit to, not how interesting a behavior is. The signed-off rules:
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- guardrails: the surfaces we commit to are bedrock guardrails, OpenAI moderations,
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the LiteLLM content filter, LLM-as-a-judge and presidio masking. Third-party vendor
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guardrails are tail and sit at P2
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- AIM stays P2 until its DRI lands a mock AIM server; there is no live AIM tenant in CI,
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so promoting it would only buy a permanently red or permanently skipped cell
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- logging: s3, GCS, prometheus, datadog and OTEL are P0 on success, failure and stream
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where the path exists. The remaining eval/analytics/cost destinations are tail at P2
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- auth: virtual keys and JWT are the committed paths at P0. OAuth2 introspection and the
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IP allowlist are P2
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- P0 + P1 is the number the team is driving to 95%; P2 rows stay enumerated so a tail gap
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is visible, but they do not gate the target
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## Status: this is a draft for review
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The cells were enumerated from the codebase and the tiers are a first proposal. Known
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things to settle before treating the set as final:
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The cells were enumerated from the codebase. Known things to settle before treating the
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set as final:
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- tiers are proposed, not signed off; 125 P0 is a lot to prove fail-before-fix, so P0 may
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want tightening
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- a few cells need a support check or a prune (for example `llm.embeddings.anthropic.*`
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and `reliability.perf.throughput.under_slo`)
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- auth is covered in two places (`other.auth.*` and the mgmt authz assertions); the
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@ -10,25 +10,25 @@
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- {id: guardrail.litellm_content_filter.apply_endpoint.allows, module: guardrail, tier: P0, hook_point: apply_endpoint, assertions: [allows], exercised_on: [chat_completions], source: "guardrail_endpoints.py:apply_guardrail", rationale: "POST /guardrails/apply_guardrail returns clean text for allowed input"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {id: guardrail.lakera.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/lakera_ai_v2.py", rationale: "Prompt-injection block pre-execution"}
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- {id: guardrail.lakera.post_call.blocks, module: guardrail, tier: P2, 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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {id: guardrail.aim.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions, messages], source: "guardrail_hooks/aim/aim.py", rationale: "Security guardrail malicious-input. P2 until the DRI lands a mock AIM server; no live AIM tenant in CI"}
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- {id: guardrail.aim.post_call.blocks, module: guardrail, tier: P2, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/aim/aim.py", rationale: "Output security check. P2 until the DRI lands a mock AIM server; no live AIM tenant in CI"}
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- {id: guardrail.ibm_guardrails.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/ibm_guardrails/ibm_detector.py", rationale: "Enterprise multi-policy"}
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- {id: guardrail.ibm_guardrails.post_call.blocks, module: guardrail, tier: P2, hook_point: post_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/ibm_guardrails/ibm_detector.py", rationale: "Output policy validation"}
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- {id: guardrail.semantic_guard.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/semantic_guard", rationale: "Semantic policy compliance"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {id: guardrail.microsoft_purview.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/microsoft_purview/purview_dlp.py", rationale: "DLP sensitive-data disclosure"}
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- {id: guardrail.headroom.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/headroom/headroom.py", rationale: "Anomaly detection threshold"}
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- {id: guardrail.generic_guardrail_api.pre_call.blocks, module: guardrail, tier: P2, 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"}
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- {id: guardrail.pangea.pre_call.blocks, module: guardrail, tier: P2, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/pangea/pangea.py", rationale: "API security + DLP"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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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- {id: guardrail.llm_as_a_judge.pre_call.blocks, module: guardrail, tier: P0, hook_point: pre_call, assertions: [blocks], exercised_on: [chat_completions], source: "guardrail_hooks/llm_as_a_judge", rationale: "LiteLLM-native judge guardrail; core supported surface, judge_model credential resolution regressed in production"}
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- {id: guardrail.litellm_content_filter.pre_mcp_call.blocks, module: guardrail, tier: P1, hook_point: pre_mcp_call, assertions: [blocks], exercised_on: [mcp_operations], source: "guardrail_hooks/litellm_content_filter/content_filter.py:_scan_mcp_tool_call_arguments", rationale: "A general content-filter guardrail configured mode=pre_mcp_call blocks a banned keyword in an MCP tool call's arguments before it reaches the upstream MCP server; a clean argument passes"}
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- {id: logging.otel.stream.exports_metric, module: logging, tier: P0, event: stream, assertions: [exports_metric], exercised_on: [chat_completions, messages, responses], source: "integrations/otel/logger.py", rationale: "Streaming closes the LLM span from the stream path; historically prone to duplicate/orphaned spans"}
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- {id: logging.otel.stream.records_ttft, module: logging, tier: P1, event: stream, assertions: [records_ttft], exercised_on: [chat_completions, messages, responses], source: "integrations/otel/mappers/genai.py", rationale: "TTFT is the streaming latency SLI; a zero or span-length value silently corrupts dashboards"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {id: logging.braintrust.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/braintrust_logging.py", rationale: "Evals platform spend"}
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- {id: logging.langsmith.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/langsmith.py", rationale: "LangChain ecosystem"}
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- {id: logging.arize.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions, embeddings], source: "integrations/arize/arize.py", rationale: "ML-ops observability"}
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- {id: logging.mlflow.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/mlflow.py", rationale: "Experiment tracking cost/run"}
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- {id: logging.opik.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/opik/opik.py", rationale: "Eval platform spend/case"}
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- {id: logging.openmeter.success.exports_metric, module: logging, tier: P2, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages, embeddings], source: "integrations/openmeter.py", rationale: "Usage metering for billing"}
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- {id: logging.literal_ai.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions, messages], source: "integrations/literal_ai.py", rationale: "Tracing platform spend"}
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- {id: logging.posthog.success.exports_metric, module: logging, tier: P2, event: success, assertions: [exports_metric], exercised_on: [chat_completions, messages], source: "integrations/posthog.py", rationale: "Product analytics batching"}
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- {id: logging.azure_storage.success.writes_object, module: logging, tier: P2, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/azure_storage/azure_storage.py", rationale: "Azure blob for enterprise"}
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- {id: logging.cloudzero.success.logs_spend, module: logging, tier: P2, event: success, assertions: [logs_spend], exercised_on: [chat_completions], source: "integrations/cloudzero/cloudzero.py", rationale: "Cost ops correlation"}
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- {id: logging.focus.success.writes_object, module: logging, tier: P2, event: success, assertions: [writes_object], exercised_on: [chat_completions, messages], source: "integrations/focus/focus_logger.py", rationale: "Cost mgmt multi-destination export"}
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- {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"}
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- {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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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {id: other.auth.virtual_key.route_group_allowed, module: other, tier: P0, area: auth, assertions: [route_group_allowed], source: "route_checks.py:106-128", rationale: "allowed_routes=[llm_api_routes] grants all LLM endpoints"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {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"}
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- {id: other.auth.oauth2.token_valid_allows, module: other, tier: P2, area: auth, assertions: [token_valid_allows], source: "oauth2_check.py:15-73", rationale: "OAuth2 introspection grants active token"}
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- {id: other.auth.oauth2.token_invalid_denied, module: other, tier: P2, area: auth, assertions: [token_invalid_denied], source: "oauth2_check.py:37-73", rationale: "Expired/inactive OAuth2 token denied"}
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- {id: other.auth.ip_allowlist.internal_ip_allows, module: other, tier: P2, area: auth, assertions: [internal_ip_allows], source: "ip_address_utils.py:54-76", rationale: "Internal CIDR bypasses public-API restriction"}
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- {id: other.auth.ip_allowlist.external_ip_denied_to_private, module: other, tier: P2, area: auth, assertions: [external_ip_denied_to_private], source: "ip_address_utils.py:54-76", rationale: "External IP cannot reach internal-only resources"}
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- {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"}
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- {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"}
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- {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"}
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