Performs comprehensive C/C++ security review for memory corruption, integer overflows, race conditions, and platform-specific vulnerabilities. Use when auditing native C/C++ applications, reviewing daemons or services for memory safety, or hunting integer overflow / use-after-free / race conditions in userspace code.
Performs comprehensive C/C++ security review for memory corruption, integer overflows, race conditions, and platform-specific vulnerabilities. Use when auditing native C/C++ applications, reviewing daemons or services for memory safety, or hunting integer overflow / use-after-free / race conditions in userspace code.
Runs in the main conversation (invoke via /c-review:c-review). Orchestrator owns the Task* ledger as bookkeeping for retries; workers and judges have no Task tools. Workers and judges are named plugin subagents (c-review:c-review-worker, c-review:c-review-dedup-judge, c-review:c-review-fp-judge); tool sets are declared in plugins/c-review/agents/*.md. Findings are exchanged via markdown-with-YAML files in a shared output directory.
When to Use
Native C/C++ application security review: memory safety, integer overflow, races, type confusion, Linux/macOS daemons, Windows userspace services.
When NOT to Use
Kernel drivers/modules (Linux, Windows, macOS).
Managed languages (Java, C#, Python, Go, Rust).
Embedded/bare-metal code without libc.
Subagents
Subagent type
Purpose
Tool set
c-review:c-review-worker
Run assigned cluster, write findings
Read, Write, Edit, Bash
c-review:c-review-dedup-judge
Merge duplicates (runs first)
Read, Write, Edit, Glob
c-review:c-review-fp-judge
FP + severity + final reports (runs second)
Read, Write, Edit, Bash
Tools come from each agent's frontmatter at spawn time. The orchestrator's Task*/Agent/Bash/etc. come from this skill's allowed-tools. Search-tool / Bash interaction: in current Claude Code, an agent granted Bash is not also granted the dedicated Globor Grep tools (the calls return No such tool available; the harness expects find/grep/rg via Bash instead). So only the dedup-judge — the one agent that holds noBash — uses Glob; the worker, fp-judge, and the orchestrator resolve and search paths with Read / Bashfind / rg / grep / test -f instead. Because the cluster/finder prompt seeds are written in ripgrep regex syntax (\s, \d, \b), Bash-holding agents must run them with rg — a plain grep -E may silently mishandle \s and return a false-empty (a bad cleared). If rg is not installed its call fails loudly (command not found) — fall back to grep -E with POSIX classes (\s→[[:space:]], drop \b), never a raw-\sgrep. Do not reintroduce Glob/Grep into a Bash-holding agent's protocol.
Architecture
coordinator: write context.md → build_run_plan.py → TaskCreate × M
→ spawn primer (foreground) → spawn M workers (parallel)
→ classify Phase-7 outcomes + write findings-index.txt
→ dedup-judge → fp-judge → report safety net (SARIF + REPORT.md) → return REPORT.md
Path convention: every later phase shells out to ${C_REVIEW_PLUGIN_ROOT}/scripts/*.py, so resolve that variable first to the plugin directory that contains prompts/clusters/buffer-write-sinks.md (and scripts/build_run_plan.py). Try in order, first hit wins:
Native Claude Code — ${CLAUDE_PLUGIN_ROOT}, accepted if Bash: ls "${CLAUDE_PLUGIN_ROOT}/prompts/clusters/buffer-write-sinks.md" resolves.
Codex — ${CODEX_PLUGIN_ROOT} (set it the same way if that var is present and resolves the marker).
Fallback search — covers Codex installs under ~/.codex, Claude installs under ~/.claude, and a local checkout / repo run: Bash: find ~/.claude ~/.codex . -path '*/plugins/c-review/prompts/clusters/buffer-write-sinks.md' -print -quit 2>/dev/null. Take the match and strip the trailing /prompts/clusters/buffer-write-sinks.md to get the root (the home dirs are searched before . so an installed copy wins over any vendored copy in the audited repo).
Set C_REVIEW_PLUGIN_ROOT to the resolved root. If all three fail, abort with a message naming the roots searched — do not enter Phase 4 with an empty variable (every python3 "${C_REVIEW_PLUGIN_ROOT}/scripts/..." call would fail with a confusing path error).
Scope convention: keep two scopes separate throughout the run:
finding_scope_root — the user-requested audit subtree. Workers may only file findings whose vulnerable location is inside this subtree.
context_roots — read-only repo roots/files workers and judges may inspect to verify reachability, callers, wrappers, build flags, mitigations, and threat-model details. Default to . unless the user explicitly forbids broader context. Reading context outside finding_scope_root is allowed; filing findings there is not.
Rationalizations to Reject
"Background spawns parallelize the workers." They do not — Agent calls in a single assistant message already run concurrently. run_in_background=true defeats the Phase 6a primer cache, so every worker pays full cache-creation (cache_read_input_tokens=0) and the ~15 K-token primer is wasted M times. This is the single most common defect — multiple recent runs spawned 7-of-8 (or all) workers with bg=true. Default: omit run_in_background from worker spawns.
"I'll re-derive the cluster list / paths / pass prefixes inline instead of running build_run_plan.py." The script is the only authority for selection and rendering. Paraphrasing it drops fields that the worker self-check requires, producing worker-N abort: spawn prompt malformed. Always run the script and Read plan.json.
"The run partially succeeded — I'll just write REPORT.md from what completed." Hiding partial runs behind a successful report is a correctness bug. If any Phase-5 cluster task is not completed, surface it prominently in run-summary.md and the final response.
"Zero findings — skip Phase 8." Always run both judges and Phase 8b: dedup-judge writes a minimal no-op dedup-summary.md on an empty index, fp-judge writes empty REPORT.md/REPORT.sarif, and Phase 8b's SARIF generator emits results: [] for the empty case. SARIF consumers depend on a stable artifact set.
"Bash: ls README* is fine for the preflight." Under zsh, an unmatched glob aborts the whole compound command before 2>/dev/null runs. Use find (never fails on no-match) — and not Glob, which is unavailable to an agent that also holds Bash.
Orchestration Workflow
Run these phases in the main conversation.
Phase 0: Parameter Collection
Entry: skill invoked. Exit:threat_model, worker_model, severity_filter resolved; scope_subpath resolved or set to "."; finding_scope_root=scope_subpath; context_roots resolved.
The skill is invoked directly (no command wrapper). Parse any free-text arguments the user passed on the /c-review:c-review line (e.g. flamenco only, high severity only, use haiku) and pre-fill the answers they imply — then ask for any missing required parameters with oneAskUserQuestion call. Never silently default the required parameters.
Required parameters:
Parameter
Values
How to infer from args
threat_model
REMOTE / LOCAL_UNPRIVILEGED / BOTH
Words like "remote", "network", "attacker" → REMOTE; "local", "unprivileged" → LOCAL_UNPRIVILEGED; otherwise ask.
worker_model
haiku / sonnet / opus
Explicit model name in args. Otherwise ask (no silent default).
Phrases like "X only", "just audit X/", "review subdirectory X" → src/X/ or the matching subdir. Apply fuzzy matching against top-level subdirectories of the repo. If absent, set "."; if ambiguous, ask.
Call AskUserQuestion exactly once with only unresolved required parameters (threat_model, worker_model, severity_filter) plus scope_subpath only when the user explicitly requested a narrowed scope but it is ambiguous. If the required parameters were all pre-filled and scope is absent or resolved, skip the question.
After resolving scope_subpath, set finding_scope_root="${scope_subpath:-.}". Set context_roots="." by default so workers can verify callers/build settings outside a narrowed subtree without filing out-of-scope findings. If the user explicitly asks to forbid broader context, set context_roots="${finding_scope_root}" and note that reachability confidence may be lower.
Probe within ${finding_scope_root:-.} with the Bash commands below (non-empty output ⇒ flag true). The dedicated Grep/Glob tools are unavailable to this orchestrator because it holds Bash — use grep/rg/find via Bash. (If a probe regex uses \s/\b and your grep lacks GNU \s support, run it with rg -uu — which honors \s and still searches ignored files — or replace \s→[[:space:]] and drop \b. Widening is safe: a false-positive flag only adds a harmless worker, a missed match would skip a pass.):
compile_commands.json is informational (no agent currently uses LSP), but the probe is mandatory so the run summary records whether richer local tooling is available. Probe via Glob: **/compile_commands.json under ${context_roots}. If Glob is unavailable, use:
printf'%s\n'"${context_roots:-.}" | tr',''\n' | while IFS= read -r root; do
[ -n "$root" ] && find "$root" -name compile_commands.json -print -quit
done | head -1
# `find "$root"` is quoted intentionally so a context root containing spaces# (e.g. "/Users/me/My Repo") survives word-splitting. Do not unquote it.
If absent, suggest CMake -DCMAKE_EXPORT_COMPILE_COMMANDS=ON/Bear/compiledb to the user but continue.
The coverage/ subdirectory holds per-worker coverage-gate audit files (coverage/worker-{N}.md). Workers write to it instead of embedding the table in their reply — see agents/c-review-worker.md step 5.
Skim README.{md,rst,txt} and any build file (Makefile, CMakeLists.txt, meson.build, configure.ac) — preflight with find (via Bash) before any Read (a Read on a missing file aborts the turn; Glob is unavailable to this orchestrator because it holds Bash). Do not use Bash: ls README* for the preflight: under zsh, an unmatched glob aborts the whole compound command before 2>/dev/null runs (observed: a Phase-3 ls src/X/README* call failed with no matches found and dropped the entire preflight). Use find . -maxdepth 2 -name 'README*' -o -name 'Makefile' -o -name 'CMakeLists.txt' -o -name 'meson.build', which never fails on no-match.
Write ${output_dir}/context.md with: YAML frontmatter (threat_model, severity_filter, scope_subpath, finding_scope_root, context_roots, is_cpp, is_posix, is_windows, output_dir, compile_commands as present/absent plus path when present), then a short markdown body with five sections — Purpose (1-3 sentences), Scope (what's in finding_scope_root, and that findings outside it are out of scope), Entry points (where untrusted data enters: network, files, CLI, IPC), Trust boundaries (sandboxed vs trusted peers vs arbitrary remote), Existing hardening (fuzzing corpora, sanitizers, privilege separation).
Phase 4: Build Run Plan (deterministic)
Entry: language flags + threat_model known; ${output_dir}/findings/ exists. Exit:${output_dir}/plan.json and ${output_dir}/worker-prompts/*.txt written; M = worker_count known.
Selection, filtering, path resolution, and spawn-prompt rendering are delegated to the script to prevent the "orchestrator paraphrases the spawn template and drops fields" failure mode:
The script writes plan.json + worker-prompts/worker-N.txt + (if --cache-primer=true, the default) worker-prompts/cache-primer.txt, and prints a JSON summary on stdout. Exits non-zero on any missing prompt — surface the message and stop. Typical M with the default --max-passes-per-worker 4 (REMOTE, is_posix=true): 13 (C POSIX), 15 (C++ POSIX), 16 (C POSIX + Windows), 18 (C++ POSIX + Windows); LOCAL_UNPRIVILEGED adds ~1 because ambient-state keeps its two REMOTE-skipped passes. After it returns, Read plan.json for the structured selection — never re-derive filtering or paths.
--max-passes-per-worker N caps the per-worker pass count. The planner deterministically splits any non-consolidated cluster with more than N passes into ceil(K/N) contiguous chunks; each chunk becomes its own c-review-worker spawn with a -{i}-suffixed cluster_id (e.g. arithmetic-type-1, arithmetic-type-2). The consolidated cluster buffer-write-sinks (13 passes) is exempt — never chunked, regardless of pass count or override — so one worker builds its shared Phase-A inventory once and runs every phase (chunking a consolidated cluster would force each chunk to rebuild that inventory, which workers skip in practice). The shared prompt-cache prefix and Cluster prompt: path are byte-identical across chunks, so the cache primer still warms every worker. Default 4 is calibrated against the heavy non-consolidated clusters in manifest.json. Some output-heavy non-consolidated clusters may declare a smaller manifest-level max_passes_per_worker override so each expensive pass group gets a smaller worker. Pass --max-passes-per-worker 0 to disable all chunking, including manifest overrides (one worker per cluster). Because buffer-write-sinks runs all 13 passes in one worker, it is the heaviest worker in the fan-out; if it ever hits the soft tool-call cap on a large codebase, surface its truncation note rather than splitting it (splitting re-introduces the inventory-skip).
Entry:${output_dir}/plan.json exists; M = plan.workers.length. Exit:cluster_task_ids[] created (1:1 with plan.workers), all pending.
The task ledger is orchestrator bookkeeping only (TUI visibility + Phase-7 retry tracking) — workers never read or write it. One TaskCreate per worker, populating metadata with kind="cluster", worker_n, cluster_id, spawn_prompt_path, pass_prefixes, attempt=1 — all values copied verbatim from plan.workers[i]. Track cluster_task_ids[] in plan.workers order.
Phase 6: Spawn workers (optional cache-primer first, then M in parallel)
Entry:cluster_task_ids[] populated; per-worker spawn prompt files exist at ${output_dir}/worker-prompts/worker-N.txt. Exit: all M Agent calls — across every wave — have returned (the parallel spawn block(s) completed).
Phase 6a: Cache primer (gated on plan.run.cache_primer)
A parallel batch from cold start cannot share cache (all M requests dispatch simultaneously, none has finished writing). To warm the prefix, spawn a tiny primer first — foreground (background spawns don't share cache with subsequent foreground spawns).
If plan.run.cache_primer == true, build_run_plan.py has written ${output_dir}/worker-prompts/cache-primer.txt. Spawn it in its own assistant message: Read the file, pass verbatim as Agentprompt with subagent_type=c-review:c-review-worker, model=${worker_model}, description="C review cache primer", no run_in_background. The script wrote the prefix byte-identical to worker-1.txt through the <context> block — that byte-identity is what gives the parallel workers their cache hit. The primer trailer contains Cache primer: true, which the worker system prompt treats as a first-class mode and returns exactly worker-PRIMER abort: cache primer (no analysis performed) in one text response with zero tool calls. Discard the abort line — Phase 7 ignores it (no worker-N id).
Foreground spawn already serializes — no sleep needed before Phase 6b. Skip Phase 6a entirely if plan.run.cache_primer == false.
Phase 6b: Spawn M real workers in parallel (one message per wave of ≤16)
STOP — read this before composing the spawn message.
Workers MUST be spawned foreground (no run_in_background field, or run_in_background=false).
"Parallel" here means one assistant message containing the wave's Agent calls — that already runs them concurrently. (For large M, split into consecutive waves of ≤16 calls, one message per wave — see "Required spawn shape" below.) Background spawns are NOT how you parallelize this skill.
Background spawns defeat Phase 6a's primer cache: every worker pays full cache-creation on its first turn (cache_read_input_tokens=0), and the primer's ~15 K tokens are wasted M times over. Two real runs (audit logs available) had exactly this symptom — every worker started with first_cr=0.
Before sending the spawn message, audit your draft: every Agent call must have norun_in_background key. If you wrote run_in_background=true, delete it.
Required spawn shape: emit a single assistant message containing the wave's Agent tool invocations — that one message is what runs them concurrently. Sequential spawning (one Agent call per message) serializes the review and is also wrong, but that failure is loud (timing); the background-spawn failure is silent (cost).
Waves when M exceeds the per-message cap. The harness caps the number of Agent calls it will dispatch from a single assistant message (observed: ~20 in Claude Code — a real 25-worker run silently kept only the first 20 and had to spawn the rest in a second message). So when M > 16, plan the waves up front: split the workers into consecutive waves of ≤16 Agent calls, each wave its own single assistant message. Rules:
Within a wave: all Agent calls in one message, foreground (no run_in_background) — identical shape to a single-wave run.
Across waves: wave k+1 is a separate message that can only be sent after wave k's Agent calls all return (a tool-use message ends the turn). Waves are therefore serialized with respect to each other — that is correct and loud; accept it.
Never reach for run_in_background=true to fit more workers in one message. More waves, never background — background defeats the primer cache (see the STOP box) and is the cardinal error this skill guards against.
Cache across waves: the primer prefix has a ~5-minute cache TTL that refreshes on every hit, so back-to-back waves keep hitting it. If a later wave will start more than ~5 minutes after the previous one (very large M), re-spawn the Phase-6a primer in its own message first to re-warm the prefix.
Balance the waves (e.g. M=25 → 13+12, not 20+5) so no wave hugs the cap and the last wave isn't a tiny straggler.
After every wave has returned, proceed to Phase 7 with the full set of M worker results.
For each worker N ∈ [1..M] (in its assigned wave):
Read: ${output_dir}/worker-prompts/worker-N.txt
Pass the file contents verbatim as the Agent tool's prompt argument:
Parameter
Value
subagent_type
c-review:c-review-worker
model
${worker_model} (haiku / sonnet / opus)
description
C review worker N
prompt
the full text of worker-N.txt (no edits)
run_in_background
field MUST be omitted, OR set to false. Never true. See the foreground-spawn warning above.
The spawn prompt is the single authority. Pass it verbatim — every field is required by the worker's self-check; any deviation triggers worker-N abort: spawn prompt malformed.
Anti-patterns to reject:
Passing run_in_background=true (the dominant historical defect — see warning above).
Cramming more than ~16 Agent calls into one message when M is large — the harness silently keeps only the first ~20 and drops the rest. Use balanced waves of ≤16, never background spawns, to cover all M.
Hand-typing the spawn prompt instead of reading worker-N.txt.
Inserting Task-related instructions ("first call TaskList", "Assigned task id: "). Workers have no Task tools.
Editing the rendered prompt before passing it (trimming "redundant" fields, collapsing pass lists).
Phase 7: Wait for Workers and Classify Outcomes
Entry: all M Phase-6 Agent calls have returned. Exit: every cluster has either succeeded or been retried up to the cap; ${output_dir}/findings-index.txt written.
The Phase-6 Agent invocations block until each worker returns. Inspect each worker's return text and apply this classifier in order — first match wins:
#
Match (in return text)
Outcome
Action
1
worker-N complete:
provisional success
Parse the wrote N finding files count, then run the artifact validator below before TaskUpdate to completed.
Stop the run, surface the abort + spawn-prompt path. Re-running the same prompt repeats the failure — pre-work-budget exhaustion always means the worker couldn't pass its self-check, which a retry won't fix.
3
other worker-N abort:
retryable
Mark pending, set metadata.abort_reason, needs_respawn=true, increment attempt.
4
Agent errored or no complete:/abort: token
retryable
Same as #3 (transient worker crash).
If any non-retryable, stop. Otherwise, before re-spawning, clear each retryable worker's prefix-space on disk — the Phase-7 index is built from disk, so a crashed attempt's higher-id stragglers (files the replacement never re-emits) would otherwise be resurrected into the report. Loop over the worker's actual pass_prefixes (from its task metadata), substituting each real prefix for ${pfx} — do not run the command with a literal PREFIX:
# zsh-safe: `find … -delete` never aborts on no-match (an `rm PREFIX-*.md` glob would).# Replace `PREFIX1 PREFIX2` with the worker's actual space-separated pass_prefixes.for pfx in PREFIX1 PREFIX2; do
find "${output_dir}/findings" -maxdepth 1 -type f -name "${pfx}-*.md" -delete
done
Then re-spawn each pending retryable with attempt <= 2 in one parallel block (cap = 2 attempts per cluster). attempt was just incremented to 2 on the first failure, so the guard must admit 2 to allow the single retry — attempt < 2 would block every retry. A second failure increments to 3, which fails <= 2 and ends retries. Replacement workers reuse deterministic finding IDs per prefix, so a cleared prefix-space plus a fresh write yields a consistent shard / coverage / disk set.
Sanity-check + write index
For every provisional complete: cluster, validate the worker-owned shard, coverage file, coverage rows, filed IDs, and claimed finding count against plan.json before marking the task completed. Run one command per completed worker, or one command with repeated flags for all provisional completions:
Do not pass bare worker-N=N arguments unless they are grouped after --claimed-count or preceded by their own repeated --claimed-count flag.
If validation exits non-zero, treat the completion as malformed and retryable (classifier row #4): mark the task pending, store the validator output in metadata.abort_reason, set needs_respawn=true, and increment attempt. Missing findings-index.d/worker-N.txt, missing coverage/worker-N.md, missing coverage rows, invalid skipped: rows, filed IDs absent from the shard or disk, and claimed-count mismatches are all malformed completions. After the retry cap, leave the cluster task incomplete and surface the validator output in run-summary.md and the final response. Only validation-clean provisional completions may be TaskUpdated to completed.
Then build the index. The canonical index is the set of finding files actually on disk, not the shard union — building from disk guarantees that a finding written without a matching shard entry (a worker that crashed between its Write and its shard-append, or the single-prefix empty-shard trap the worker prompt warns about) is still picked up by dedup → fp-judge → REPORT/SARIF instead of silently vanishing, and that every index entry resolves to a real file:
# Canonical index = every finding file on disk. `find` never fails on no-match# (an empty findings/ yields an empty index — the unambiguous "zero findings"# signal). `sort -u` collapses Phase-7 retry duplicates: replacement workers reuse# deterministic ids, so the same path appears once.
find "${output_dir}/findings" -maxdepth 1 -type f -name '*.md' 2>/dev/null \
| sort -u > "${output_dir}/findings-index.txt"# Reconcile against the per-worker shards: any path on disk but in NO shard is an# orphan whose worker failed to record it. It is already in the index above (so it# is NOT dropped) — print it so the bookkeeping gap can be surfaced. Non-fatal.if [ -d "${output_dir}/findings-index.d" ]; then# Reconcile by basename (finding ids are unique), so a path-format difference# between the worker `find` and this one (trailing slash, /var↔/private/var)# cannot manufacture false orphans. Any basename on disk but in no shard is an# orphan whose worker failed to record it.comm -13 \
<(find "${output_dir}/findings-index.d" -maxdepth 1 -type f -name 'worker-*.txt' -exec awk 1 {} + 2>/dev/null | sed 's#.*/##; /^[[:space:]]*$/d' | sort -u) \
<(find "${output_dir}/findings" -maxdepth 1 -type f -name '*.md' 2>/dev/null | sed 's#.*/##' | sort -u)
fi
The shards stay the per-worker audit trail (validate_artifacts.py checks them) and the dedup-judge's crash-recovery fallback, but they no longer gate what reaches the pipeline. For each orphan basename the reconcile prints, map its <PREFIX> to the owning worker via plan.json and note in run-summary.md that that worker's shard was incomplete — the finding is already in the index (so it is not lost), but the bookkeeping gap should be visible. Still cross-check the index line count against the sum of wrote N worker claims; log mismatches but don't abort.
After task updates and index creation, run TaskList and write ${output_dir}/run-summary.md with:
findings-index.txt line count and any mismatch against worker claims
judge status once Phase 8 finishes, or the reason a judge was skipped/failed
If any Phase-5 cluster task is not completed — or any worker returned a complete: line carrying the truncated at hard cap token (it hit the tool-call cap before searching every pass; its coverage file will show one or more cleared (NOT SEARCHED — truncated at hard cap) rows) — include it prominently in run-summary.md and the final response. A hard-cap-truncated worker is marked completed for ledger purposes but is a partial result: do not let that completed status hide the incomplete coverage behind a successful report.
Always run Phase 8 even on zero findings — both judges short-circuit on an empty index: dedup-judge writes a minimal no-op dedup-summary.md, and fp-judge writes empty REPORT.md/REPORT.sarif so SARIF consumers get a stable artifact set.
Entry:findings-index.txt exists. Exit: dedup-judge and fp-judge have returned; dedup-summary.md, fp-summary.md, REPORT.md, and ideally REPORT.sarif are written.
Each judge's full protocol is its system prompt (agents/c-review-{dedup,fp}-judge.md); spawn prompts pass only per-run variables. Do not reference prompts/internal/judges/ — those files don't exist.
STOP — these two judges run in SEQUENCE, not in parallel. Unlike the Phase-6b workers (which you spawn as M Agent calls in one message precisely because that runs them concurrently), the judges have a hard data dependency: fp-judge must see the merged_into / also_known_as annotations dedup-judge writes, and it only skips files already carrying merged_into. If you emit both Agent calls in one message they run concurrently — fp-judge reads findings before any merge annotations exist, judges every duplicate as a separate primary, and (because dedup-summary.md doesn't exist yet) trips its "dedup did not run" fallback, producing an inflated, duplicated REPORT.md/SARIF.
Spawn dedup-judge in its own assistant message, wait for its dedup-judge complete: (or abort:) return, then spawn fp-judge in a separate message. Before composing the fp-judge spawn, confirm dedup finished — Bash: test -f ${output_dir}/dedup-summary.md must succeed (or you saw the dedup complete: token). Never put both judge Agent calls in the same message.
First message — Agent(subagent_type="c-review:c-review-dedup-judge", description="Dedup judge", prompt=f"output_dir: {output_dir}"). Wait for its return and classify it (below) before continuing.
Then, in a separate message — Agent(subagent_type="c-review:c-review-fp-judge", description="FP + severity judge", prompt=f"output_dir: {output_dir}\nsarif_generator_path: {sarif_generator_path}") — resolve sarif_generator_path to ${C_REVIEW_PLUGIN_ROOT}/scripts/generate_sarif.py.
Judge failure handling. Same shape as Phase 7's classifier, applied to judge return text:
… complete: → success.
… abort: → non-retryable for that judge. Surface the abort line plus ls -l ${output_dir}/findings-index.txt, then still run Phase 8b (its SARIF + REPORT.md safety net guarantees the artifact set even when a judge aborts), and stop without spawning further judges. "Stop" means do not continue the judge pipeline — it does not mean skip Phase 8b.
No complete: (help message / error / question) → retryable once.SendMessage(to=<agentId>, …) rather than a fresh spawn (the agent already paid the protocol-parse cost). Include the explicit finding paths from findings-index.txt. If the second try still fails, surface the transcript and continue to Phase 8b.
Phase 8b: Report safety net (SARIF + REPORT.md)
Entry: fp-judge returned, or the run aborted early. Exit:${output_dir}/REPORT.sarif and ${output_dir}/REPORT.md both exist.
test -d "${output_dir}/findings" && python3 "${C_REVIEW_PLUGIN_ROOT}/scripts/generate_sarif.py""${output_dir}"
Run the SARIF generator unconditionally whenever findings/ exists — it is idempotent (full overwrite), emits results: [] for zero-survivor runs, and handles partial runs (findings without fp_verdict are emitted as LIKELY_TP, exempt from the severity_filter since their severity was never judge-validated, and marked unjudged: true / severity_validated: false with an [UNVALIDATED SEVERITY — not judged] message prefix — so an inferred severity guess can never silently drop them under a medium/high filter). Always overwriting protects against an fp-judge that crashed mid-write and left a corrupt REPORT.sarif on disk.
If the generator prints a WARNING: skipped N … line on stdout (it also records invocations[].properties.skipped_findings in the SARIF and a warning notification per dropped file), one or more finding files were unreadable or had no parseable frontmatter and were excluded from the report. This is a dropped result — surface it prominently in run-summary.md and the final response with the count and paths, the same way a non-completed cluster task is surfaced. Do not let the otherwise-clean SARIF hide the loss.
Then guarantee REPORT.md exists. Unlike SARIF (mechanical), REPORT.md is the fp-judge's curated artifact, so do not overwrite a judge-written one. (The fp-judge writes REPORT.md with a Bash heredoc, not the Write tool, because the harness blocks the Write tool for subagent report files — do not "fix" the judge by re-mandating Write. The orchestrator is the main agent and is not subject to that block, so its own Write below works.) Check for it, and if it is missing (the judge crashed, even its Bash-heredoc write failed, or it returned the report as chat text instead of writing the file), the orchestrator writes REPORT.md itself rather than failing the run:
If the fp-judge returned the report body in its transcript, Write that text verbatim to ${output_dir}/REPORT.md.
Otherwise synthesize it from the on-disk findings: take the survivor primaries (fp_verdict ∈ {TRUE_POSITIVE, LIKELY_TP}, no merged_into; if the judge never ran, treat a finding with no fp_verdict as a survivor) listed in findings-index.txt, apply severity_filter from context.mdto judged survivors only — unjudged findings (no fp_verdict) are included regardless of filter and rendered under an Unvalidated (severity not judged) section with a [UNVALIDATED SEVERITY — not judged] label, mirroring the SARIF behavior so a strict filter never silently drops them — and Write a REPORT.md mirroring the fp-judge template — YAML frontmatter (stage: final-report, threat_model, severity_filter, total_primaries, reported_findings), a severity-distribution table, then one section per reported finding grouped by severity (embed the Description / Code / Data flow / Impact / Recommendation body for CRITICAL/HIGH; reference the finding file for MEDIUM/LOW).
Either way, note in ${output_dir}/run-summary.md that REPORT.md was orchestrator-synthesized (not judge-authored). Skip the SARIF generator and this check only if ${output_dir}/findings/ doesn't exist (Phase 2 failed). After this phase, update ${output_dir}/run-summary.md with judge / SARIF / report status.
Phase 9: Return Report
Entry: Phase 8b complete. Exit: every item in Success Criteria verified true; REPORT.md returned to the caller.
Before composing the response, walk the Success Criteria checklist below and confirm each bullet against on-disk artifacts (TaskList for cluster tasks, ls/Read for the files). If any criterion fails, surface the failure prominently in the response — do not hide a partial run behind a successful report.
Then Read ${output_dir}/REPORT.md and return its content to the caller. Append an Artifacts list pointing at findings/, findings-index.txt, run-summary.md, dedup-summary.md, fp-summary.md, REPORT.md, REPORT.sarif.
Worker — base fields (id, bug_class, title, location, function, confidence, worker) + seven body sections.
Dedup-judge — adds merged_into on duplicates, or also_known_as + locations on primaries that absorbed.
FP+Severity judge — adds fp_verdict + fp_rationale on every primary; on survivors (TRUE_POSITIVE/LIKELY_TP) also adds severity, attack_vector, exploitability, severity_rationale.
Bug classes / clusters
Authoritative: prompts/clusters/manifest.json. 47 always-on bug classes, up to 64 with all conditional clusters enabled. buffer-write-sinks is fully consolidated (its sub-prompts are not re-read at runtime).
Success Criteria
The phase exits already cover most of this; the orchestrator-visible end-state is:
Every Phase-5 cluster task is completed (verify via TaskList).
${output_dir}/run-summary.md exists and records resolved scope/context, compile-commands probe result, worker claims vs index count, task status, and judge/SARIF status.
Every primary finding (no merged_into) has fp_verdict + fp_rationale; every survivor (TRUE_POSITIVE/LIKELY_TP) also has severity, attack_vector, exploitability, severity_rationale.
REPORT.md exists, severity-filtered per severity_filter (Phase 8b safety net guarantees this even when the fp-judge fails to write it).
REPORT.sarif exists (Phase 8b safety net guarantees this).
