execution-grounded-review

Execution-Grounded Review

A normal review reads the diff and asks "does this look right?" — and an implementation can look complete while a criterion silently fails. This skill refuses to grade an implementation on appearance: it runs the suite first, then traces each acceptance criterion to execution evidence — a test that actually exercised it, or observed behaviour — and marks anything it cannot back with execution as UNVERIFIED rather than passing it on faith.

It is the execution-grounded verifier in the agent-patterns review family: where adversarial-review attacks a design for faults and cold-read-gate measures whether text survives a reader, this skill verifies that running code meets its stated acceptance criteria. It is the reusable independent verifier a judgement-based loop gate delegates to (.claude/rules/loop-integrity.md, Pillar 1).

When to Use This Skill

Use this skill when...	Use something else instead when...
Verifying an implementation meets explicit acceptance criteria, proven by running it	First-pass review of a diff → code-quality-plugin:code-review
Gating a loop/phase done on an independent check of behaviour	Red-teaming a design or ADR for faults → agent-patterns-plugin:adversarial-review
Confirming a fix actually fixes the reported failure (not just compiles)	Checking premises/facts before work starts → agent-patterns-plugin:verify-before-plan
Closing the loop on "is every requirement actually covered by a test?"	Legibility of outward text → agent-patterns-plugin:cold-read-gate

The Stance

Move	What it means
Execute first	Run the full suite + typecheck + lint before any verdict. A criterion is PASS only with execution evidence — never "the code looks like it does this".
Trace each criterion	One ledger row per acceptance criterion: premise → evidence (file:line / test name / observed output) → verdict.
No silent pass	A criterion with no execution backing is UNVERIFIED (a coverage gap to surface), not an assumed pass.
Match the production sequence	For a round-trip / determinism / reproducibility / idempotence claim, a passing test is evidence only if its operation sequence reproduces the real production call path — not a convenient shorter one (see Step 3a).
Intent-starved verifier	The isolated verifier reads the criteria, the diff, and the captured execution evidence — not the author's plan narrative or rationale, which would let it rationalise a pass.
Bounded loop	One revise round on fail; a third means a structural problem the gate can't resolve.

Model is opus — like adversarial-review, the inverse of cold-read-gate: building an accurate requirement→evidence ledger is a reasoning task.

Parameters

Parse $ARGUMENTS:

• Target (first positional) — what to verify: a path, a PR ref (#123 or URL), explicit files, or absent. If absent, default to the current change (git diff HEAD + staged) and say so.
• --criteria <file> (optional) — a file of acceptance criteria. If absent, gather criteria from the task/plan in context (the acceptance criteria stated for this change) and echo them back before verifying, so the user can correct the list the skill is grading against.

Execution

Execute this execution-grounded verification:

Step 1: Run the suite first

Before reading the diff for "correctness", establish ground truth by execution. Detect and run the project's full suite + typecheck + lint, capturing output to a scratch file (this is the execution evidence the verifier grades against):

Stack	Suite	Typecheck	Lint
Node/TS	npm test (or npx vitest run)	npx tsc --noEmit	npx biome check
Python	uv run pytest -q	uv run ty check	uv run ruff check
Rust	cargo test	cargo check	cargo clippy
Go	go test ./...	go vet ./...	—

Record the exit codes and failing-test names. A red suite is itself an independent signal — a failing test does not care how hard the author worked (.claude/rules/loop-integrity.md).

Step 2: Name the criteria

State, in one numbered list, the acceptance criteria under verification (from --criteria or context). If the list is empty, stop and ask for it — there is nothing to ground a verdict in. Each criterion is one ledger row in Step 3.

Step 3: Dispatch the intent-starved verifier

One Agent, model: opus, reading only the criteria, the diff, and the captured execution-evidence file — not the author's reasoning. Template:

subagent_type: general-purpose
model: opus
prompt: |
  You verify whether an implementation meets its acceptance criteria, grounded
  in EXECUTION EVIDENCE. Read ONLY these inputs (no other files, no repo
  exploration beyond resolving evidence cited below):
    - Acceptance criteria: <numbered list from Step 2>
    - The change under review: <diff / file paths>
    - Execution evidence (suite/typecheck/lint output): <scratch file path>

  Do NOT read the author's plan, commit narrative, or rationale — grade the
  behaviour, not the intent.

  Build a ledger with ONE row per criterion:
    CRITERION=<n: the criterion text>
    EVIDENCE=<the test name / file:line / observed output that demonstrates it,
              drawn from the execution evidence — or "none">
    VERDICT=PASS|FAIL|PARTIAL|UNVERIFIED
      PASS        — execution evidence demonstrates the criterion holds
      FAIL        — execution evidence demonstrates it is violated (name the
                    concrete failing input/test)
      PARTIAL     — covered for some inputs, a stated edge case is unhandled
      UNVERIFIED  — no execution exercises this criterion (a COVERAGE GAP; do
                    NOT pass it on the basis that the code "looks right")

  Then:
    COVERAGE=<#criteria with PASS/FAIL evidence> / <total criteria>
    VERDICT: exactly one of `pass` | `fail`.
      `pass` requires every criterion PASS with execution evidence.
      Any FAIL, or any UNVERIFIED criterion, makes the overall verdict `fail`.
  Cite evidence for every row. Your final message is the deliverable.

For several independent targets, dispatch one verifier per target in a single-message parallel Agent batch — except on a [1m] model, where the concurrent-subagent rate-limit caveat applies (skill-fork-context.md); run those sequentially. Do not set context: fork — the caller needs the ledger in the main context to act on it.

Step 3a: Match the test's operation sequence to production

"A passing test exists for this claim" is not sufficient evidence for a round-trip, determinism, reproducibility, or idempotence claim. The test can pass while the design is broken, because a narrower hand-built repro silently avoids the exact ordering that would expose a divergence. The tell is when the test's sequence of operations differs from the real call path production uses.

So for any such claim, add a step to the verifier's brief:

Identify what real call sequence exercises this claim in production, and confirm the test under review reproduces that sequence — not just a convenient shorter one.

Stateful / RNG-dependent code is the high-risk class — lazy initialization, global mutable RNG state, and caching all defer or share observable state, so when an operation runs relative to its neighbours changes the result. A test of the shape construct → forward immediately and a production path of construct → generate batches (consuming lazy RNG) → first forward draw their deferred state at the same relative point in each stream, so the round-trip "works" with no error — while a real trained model's reload diverges. The passing test is real; it just exercises the one ordering that can't see the bug.

Grade such a claim UNVERIFIED until the test reproduces the production sequence, even though a green test exists.

Step 4: Triage against over-correction

The verifier grades strictly, so guard both failure modes before acting — neither talk yourself into passing broken code, nor into failing correct code:

Act on it	Drop it
A FAIL with a named failing test/input	A FAIL on a requirement the spec never stated
An UNVERIFIED criterion → write/run the missing test, then re-grade	An UNVERIFIED on behaviour outside the change's responsibility
A PARTIAL where a stated edge case is unhandled	Style/preference dressed up as a criterion failure
A coverage gap on a load-bearing criterion	A hypothetical input the contract makes impossible
A round-trip/determinism test whose sequence diverges from production (Step 3a)	A sequence difference that provably can't affect the claim's outcome

Step 5: Report and bound the loop

Emit the ledger: target, per-criterion rows with evidence, COVERAGE, and the overall verdict. Apply or hand off the genuine fixes (closing UNVERIFIED rows by adding the missing test counts as a fix). Re-run from Step 1 only if the verdict was fail; do not loop more than twice — a third round means a structural problem the gate can't resolve, which is the signal to surface to a human, not to keep grinding.

Anti-patterns

Mistake	Correct approach
Grading the diff without running anything	Execute first (Step 1) — appearance is not evidence
Passing a criterion because the code "looks like it does that"	No execution evidence → UNVERIFIED, not pass
Passing a round-trip/determinism claim because "a test exists and passes"	Confirm the test's operation sequence matches the production call path (Step 3a)
Feeding the verifier the author's plan/rationale	Intent-starved inputs — criteria + diff + execution evidence only
Inventing requirements the spec never stated	Triage (Step 4) — FAIL only on listed criteria
Looping until the verifier goes quiet	One revise round; persistent fail = structural problem

Agentic Optimizations

Context	Command
Verify current change, no target given	git diff HEAD as the target; state the default
Verify a PR	gh pr view <N> --json title,body,files then diff
Capture execution evidence	npm test -- --bail=1 2>&1 | tee /tmp/evidence.txt (or uv run pytest -q)
Single target, isolated verifier	One Agent(subagent_type: general-purpose, model: opus)

Related

• adversarial-review — attacks a design for faults; this skill verifies running behaviour against criteria
• verify-before-plan — verifies premises before work; this verifies outcomes after
• cold-read-gate — the isolation + triage + bounded-loop pattern this skill reuses (legibility lens; uses haiku)
• code-quality-plugin:code-review — the first-pass review this layers on top of
• workflow-orchestration-plugin:workflow-checkpoint-refactor — a loop whose phase gate delegates its independent verdict here
• .claude/rules/loop-integrity.md — Pillar 1: a loop's stop condition is judged by an independent verifier like this one, not the worker