implementation-final-review

A final, independent review process for code changes before implementation is declared complete. It checks the full change against the original request and the project’s rules.

In plain words
What is it for?
Use it to review a complete repository diff, including staged, unstaged, committed, and newly created task files. It is intended for changes that affect behavior or when project instructions require a final review.
Why use it?
It helps catch missed requirements, unsafe behavior, lifecycle problems, security issues, and unnecessary complexity. It also prevents the person who wrote the change from being its only reviewer.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/openai/openai-agents-python/implementation-final-review
Any agent
npx skills add openai/openai-agents-python --skill implementation-final-review
Clone the repo
git clone --depth 1 https://github.com/openai/openai-agents-python

Made for: Claude Code, Codex.

Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 10,111 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00058 $0.10111
Opus 5 $0.00029 $0.05056
Sonnet 5 $0.00012 $0.02022
Haiku 4.5 $0.00006 $0.01011

Measured 2d ago against content hash 55046b1e51b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implementation-final-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/review_protocol.py, scripts/review_state.py, scripts/test_review_protocol.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.agents/skills/implementation-final-review/SKILL.md · 209 lines

How it starts

The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Implementation Final Review

Treat implementation and final review as separate phases. Reconstruct the change from the original requirement and the complete diff; do not defend the current design merely because it is implemented or tested.

Non-negotiable guarantees

  • Review the exact final task content, including committed, staged, unstaged, and task-owned untracked deliverables. The only exceptions are the narrowly verified final-gate type-erasure and base-advance closures in step 20, which preserve clean credit through explicit identity evidence and still require the complete final verification stack on the resulting fingerprint.
  • Use the merge-base three-dot diff for patch ownership and the latest release tag separately for released compatibility.
  • Require independent review. A same-context self-review cannot satisfy the clean-review gate.
  • Freeze task-owned content while reviewers inspect a fingerprint.
  • Treat an exact normalized file path in the task and component manifests as authoritative even when ignore rules match that file. An existing exact file takes literal precedence over Git pathspec metacharacters; use explicit :(glob) magic when pattern semantics are intended. A directory or glob pathspec never promotes ignored operational files into the review.
  • Require the repository and every initialized submodule index to have no unresolved merge stages before fingerprinting.
  • Require every initialized submodule, including nested submodules, to be clean and checked out at the commit recorded by its parent index before freezing review state. Stage reviewable gitlink pointer changes in the parent repository; fail closed on dirty worktrees, hidden index flags, ignored nested changes, and untracked embedded repositories. Reject cyclic or aliased submodule worktree graphs before recursive inspection.
  • Require two consecutive identical observations of HEAD, status, diffs, task and repository workspace content, and component workspace content before accepting a review-state snapshot. Fail closed when repository state changes during capture.
  • Reject task-owned filesystem entries that Git cannot represent as finite blobs, including FIFOs, sockets, and devices.
  • Require packet, ledger, manifest, receipt, reviewer-output, and evidence paths to resolve to finite regular files. Canonicalize each path before opening. Verify the file type after opening and read content from that same descriptor; never authorize a path with stat and then reopen it. Reject evidence, receipt, and current-versus-prior ledger aliases by the opened descriptor's device and inode identity. Before accepting reviewer output or a reusable receipt, re-read the packet and current and prior ledgers and require their validated digests to remain unchanged; also re-read the indexed receipt before reporting it reusable. Materialize devices, FIFOs, sockets, or generated streams into regular files before validation.
  • Bind every canonical root-owned evidence ID and inventory ID in the ledger with contract_evidence_sha256 and inventory_sha256. Preserve those digest bindings across rounds so an existing ID cannot change content; inventory digests exclude only the ID itself so a renamed copy is not new semantic inventory.
  • Count evidence or inventory as new for a canonical root only when its digest is absent from that root's prior ownership. A new root proposal requires an evidence digest absent from every canonical root and every distinct root proposed in the same output; it cannot reuse canonical inventory before implementer promotion. Require every credited receipt to have a unique content digest and exact command.
  • Require unique keys and standard finite numbers in every JSON object. Duplicate keys, JavaScript-style NaN or infinity constants, and numeric exponents that overflow to infinity are invalid. Convert runtime numeric-size and nesting-limit failures into protocol errors instead of leaking parser exceptions.
  • Give the two reviewers distinct normalized primary and high-risk specialties, and require every preflight command to be unique before any receipt can claim it.
  • Encode manifests.dependency_map as an object that maps every component name to a nonempty array of exact pathspec and reason records. Reject prose-only claims, missing components, empty dependency sets, duplicate pathspecs, and extra record fields.
  • Treat verification receipts, reviewer outputs, findings, root-cause evidence, unchecked-inventory records, and sibling-scenario scans as exact schemas. Reject unknown fields instead of ignoring potentially conflicting evidence.
  • Repeat commit-hook inspection, every safe rewriting step, second-pass idempotence, and generated-provenance validation before every fingerprint freeze, including post-fix and delta-review rounds. Record the exact executable inspection and rewriting commands plus their results in packet preflight evidence; a prose label is not an executable command.
  • Start independent reviewers without inherited conversation history. Fresh judgment does not require repeatedly replaying the implementer's context.
  • Report only concrete, patch-scoped findings supported by requirements, released behavior, a durable boundary, explicit maintainer intent, user reliance, or a baseline regression.
  • Never weaken final repository verification. Component-aware review invalidation reduces repeated review, not required build or test gates.
  • Keep one task-global round ledger across pauses, compaction, handoff, renaming, resumed work, and post-completion feedback. Enforce a bounded budget for each active review cycle without discarding earlier history.
  • Trust the active implementation control plane to record actual reviewer dispatches, waits, outputs, and verification executions. The local protocol helper validates those records but does not replace platform-issued cryptographic execution attestation.

Read the full file on GitHub · 209 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 209 lines · 58 tokens per session scan A 55046b1e51b0

Subscribe to this mod's changes

implementation-final-review is a skill published in the GitHub repository openai/openai-agents-python (29,123 stars, last pushed yesterday), licensed MIT. It adds 58 tokens to every session and 10,111 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories