Use raw sandbox reads for memory and skills, keep line-numbered reads focused on display, and share retry-delay handling across agent and LLM code.
Trim task tool descriptions, bound multi-file read concurrency, restore Docker's text read path, and add the reviewed implementation plan docs.
## Summary
OpenAI-profile agents now receive `apply_patch` as a Codex-compatible
freeform custom tool instead of a JSON function with a `patch` field.
The model sends raw patch text validated by the vendored Lark grammar,
and Fabro round-trips OpenAI custom tool calls/results through the
Responses API.
## What Changed
- Added `fabro-llm` support for function and custom tool definitions
while preserving existing JSON function behavior for normal tools.
- Translated OpenAI custom tool calls, custom tool outputs, and
streaming `response.custom_tool_call_input.delta` events into Fabro tool
calls with raw arguments.
- Ported the Codex apply-patch grammar and adapted Codex-style patch
parsing/application semantics to Fabro's `Sandbox` trait, including
strict envelopes, fuzzy context matching, move/delete/add/update
behavior, trailing-newline normalization, and Codex-style
summaries/errors.
- Updated OpenAI agent prompt/tool registration so `apply_patch` is
freeform, and skipped JSON-schema validation/repair for custom tool
calls only.
- Updated file tracking to read Codex-style `A`/`M` result lines from
successful patch output.
## Verification
- `cargo nextest run -p fabro-llm -p fabro-agent`
- `cargo +nightly-2026-04-14 fmt --check --all`
- `cargo +nightly-2026-04-14 clippy --no-deps -p fabro-llm -p
fabro-agent --all-targets -- -D warnings`
- `git diff --check`
Note: the full non-`--no-deps` clippy command still surfaces an
unrelated existing `fabro-sandbox` `large_enum_variant` warning in
`lib/crates/fabro-sandbox/src/sandbox_spec.rs`.
---
[](https://github.com/EveryInc/compound-engineering-plugin)
🤖 Generated with GPT-5 via [Codex](https://openai.com/codex)
## Summary
Run cancellation now reaches in-flight agent work instead of waiting for
an agent stage to finish or recording cancellation as a failed stage.
The workflow cancellation primitive is now
`tokio_util::sync::CancellationToken`, with child tokens passed through
setup, handlers, manager-loop child runs, sandbox streaming commands,
CLI agent invocations, and API agent sessions.
### Plan Summary
- Promote run cancellation to `CancellationToken` while keeping stall
timeout separate.
- Route CLI agents through cancellable sandbox streaming with optional
timeouts.
- Bridge run cancellation into API sessions and preserve
`Error::Cancelled` propagation.
- Add typed events/projections for CLI cancellation and timeout.
## Cancellation flow
```mermaid
flowchart TB
RunToken[Run CancellationToken]
Executor[Core executor]
Services[RunServices]
Manager[Manager-loop child run]
CLI[Agent CLI backend]
API[Agent API backend]
Sandbox[Sandbox streaming exec]
Session[fabro-agent Session]
RunToken --> Executor
RunToken --> Services
Services -- child_token --> Manager
Services -- child_token --> CLI
CLI -- child_token --> Sandbox
Services --> API
API -- bridge guard --> Session
```
## What changed and why
- `RunOptions`, `RunServices`, core `ExecutorOptions`, CLI/server run
state, and detached-run guards now use `CancellationToken` instead of
`Arc<AtomicBool>`. Dropping services or tokens still does not mean
cancellation; only explicit `.cancel()` does.
- Manager-loop child workflows are given child tokens so parent
cancellation propagates down, while stop/max-cycle cancellation remains
scoped to the child workflow.
- Stall timeout remains intentionally separate as a stall token and
still returns `Error::StallTimeout { node_id }`, not `Error::Cancelled`.
- Agent, prompt, human, fan-in, and parallel handler paths now pass
cancellation tokens through and avoid converting `Error::Cancelled` into
normal failed outcomes.
## Agent backend behavior
CLI-mode agents no longer launch detached `setsid` jobs with temp
stdout/stderr/exit-code polling. They run through
`Sandbox::exec_command_streaming` with a child token; a missing node
timeout passes `None` to preserve the existing unbounded agent runtime,
while explicit node timeouts still apply. Cancelled CLI runs emit
`agent.cli.cancelled`, clean temp files, and return `Error::Cancelled`;
timed-out CLI runs emit `agent.cli.timed_out` and return a handler
timeout error; `agent.cli.completed` remains natural-exit only.
API-mode agents install a per-invocation `SessionCancelBridgeGuard`
after acquiring a fresh or cached session. The guard maps the run token
into the session interrupt reason and session cancel token, and aborts
stale bridge tasks before session replacement or cache reinsertion so
reused sessions are not tied to old run tokens. `Session::initialize`
now returns `Result`, and project-doc, skill, MCP, and environment
discovery paths check cancellation and pass child tokens to sandbox
commands.
## Sandbox and event model
`Sandbox::exec_command_streaming` now accepts `Option<u64>` for timeout.
Production streaming implementations use a pending future for `None`
instead of a giant sleep, while the trait fallback maps `None` to
`u64::MAX` only when delegating to non-streaming `exec_command`.
The run event model now includes typed `agent.cli.cancelled` and
`agent.cli.timed_out` payloads with stdout, stderr, and duration, plus
conversion and projection support. OpenAPI/client regeneration was
unnecessary because the API schema already models run events with a free
event string and arbitrary properties; only Rust event types changed.
## Reviewer notes
Expect signature churn around `Session::initialize`,
`CodergenBackend::run`, `RunOptions.cancel_token`,
`StartServices.cancel_token`, and `Sandbox::exec_command_streaming`. The
main behavioral checks are that user cancellation reaches in-flight
CLI/API work and that timeout/stall paths remain distinct from user
cancellation.
### Fabro Details
<details>
<summary>Ran 9 stages in 117m 40s for $150.32</summary>
| Stage | Duration | Cost | Retries |
|---|---|---|---|
| start | 0s | – | 0 |
| toolchain | 1s | – | 0 |
| preflight_compile | 2m 8s | – | 0 |
| preflight_lint | 2m 13s | – | 0 |
| implement | 77m 12s | $56.78 | 0 |
| simplify_opus | 18m 5s | $5.83 | 0 |
| simplify_gpt | 15m 33s | $87.71 | 0 |
| verify | 1m 48s | – | 0 |
| fmt | 2s | – | 0 |
| **Total** | **117m 40s** | **$150.32** | **0** |
</details>
<details>
<summary>Ran <code>ImplementPlan.fabro</code> (12 nodes and 15
edges)</summary>
```dot
digraph ImplementPlan {
graph [
goal="Implement and simplify",
model_stylesheet="
* { model: claude-opus-4-7; }
"
]
rankdir=LR
start [shape=Mdiamond, label="Start"]
exit [shape=Msquare, label="Exit"]
toolchain [label="Toolchain", shape=parallelogram, script="command -v cargo >/dev/null || { curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y && sudo ln -sf $HOME/.cargo/bin/* /usr/local/bin/; }; cargo --version 2>&1", max_retries=0]
preflight_compile [label="Preflight Compile", shape=parallelogram, script="cargo check -q --workspace 2>&1", max_retries=0]
preflight_lint [label="Preflight Lint", shape=parallelogram, script="cargo +nightly-2026-04-14 clippy -q --workspace --all-targets -- -D warnings 2>&1", max_retries=0]
fix_lints [label="Fix Lints", prompt="The preflight lint step failed. Read the build output from context and fix all clippy lint warnings.", max_visits=3]
implement [label="Implement", prompt="Read the plan file referenced in the goal and implement every step. Make all the code changes described in the plan. Use red/green TDD."]
simplify_opus [label="Simplify (Opus)", prompt="@prompts/simplify.md"]
simplify_gpt [label="Simplify (GPT-55)", prompt="@prompts/simplify.md", model="gpt-55"]
verify [label="Verify", shape=parallelogram, script="cargo +nightly-2026-04-14 clippy -q --workspace --all-targets -- -D warnings 2>&1 && cargo nextest run --cargo-quiet --workspace --status-level fail 2>&1 && cargo dev docs refresh 2>&1 && cargo dev docs check 2>&1", goal_gate=true, retry_target="fixup"]
fixup [label="Fixup", prompt="The verify step failed. Read the build output from context and fix all clippy lint warnings, test failures, and generated docs errors.", max_visits=3]
fmt [label="Format", shape=parallelogram, script="cargo +nightly-2026-04-14 fmt --all 2>&1", max_retries=0]
start -> toolchain
toolchain -> preflight_compile [condition="outcome=succeeded"]
toolchain -> exit
preflight_compile -> preflight_lint [condition="outcome=succeeded"]
preflight_compile -> exit
preflight_lint -> implement [condition="outcome=succeeded"]
preflight_lint -> fix_lints
fix_lints -> preflight_lint
implement -> simplify_opus -> simplify_gpt -> verify
verify -> fmt [condition="outcome=succeeded"]
verify -> fixup
fixup -> verify
fmt -> exit
}
```
</details>
⚒️ Generated with [Fabro](https://fabro.sh)
---------
Co-authored-by: Fabro <noreply@fabro.sh>
Co-authored-by: Bryan Helmkamp <bryan@brynary.com>
Move the built web bundle into an embedded fabro-spa crate so Cargo and
release builds no longer depend on Bun at build time, and preserve the
local dev override path for fast UI iteration.
At the same time, rename interview and agent-level aborted flows to
interrupted, keep cancelled for run-level shutdown, and stop reporting
skipped answers as interruptions in the run event stream.
Introduce a reusable Warning { kind, message, details } variant in
AgentEvent so non-fatal warnings (context window usage, deprecation,
etc.) share a single event shape. The context_window warning preserves
all original fields inside the JSON details object.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replaces set_subagent_manager() with an Option parameter on the
constructor so the dependency is explicit at creation time.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The capabilities() method was removed from the trait but the README
still listed it with an incorrect return type.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Move model facts (knowledge_cutoff, context_window) to fabro-model catalog as
source of truth. Move request-shaping (auto-thinking, 1M beta headers, Gemini
safety settings) into fabro-llm adapters. Delete ProfileCapabilities struct and
all dead code (supports_reasoning, supports_streaming, supports_parallel_tool_calls,
OpenAiProfile.reasoning_effort). Fix "powered by OpenAI" mislabeling for
Kimi/ZAI/Minimax/Inception providers.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
