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.
npx agentmods add skills/assisjp/specflow/code-reviewnpx skills add assisjp/specflow --skill code-reviewgit clone --depth 1 https://github.com/assisjp/specflowWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00105 | $0.01706 |
| Opus 5 | $0.00053 | $0.00853 |
| Sonnet 5 | $0.00021 | $0.00341 |
| Haiku 4.5 | $0.00011 | $0.00171 |
Grade A, and why
code-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.
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.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
A two-axis review of the diff between HEAD and a fixed point the user supplies:
- Standards — does the code follow the repo's documented standards and avoid known code smells?
- Spec — does the code faithfully implement the originating issue / spec?
The two axes run as parallel sub-agents so they do not pollute each other's context, then this skill aggregates their findings without merging them.
Process
1. Pin the fixed point
Use whatever the user gave — a SHA, branch, tag, main, HEAD~5. If none, ask.
Capture the diff once with three-dot (compares against the merge-base): git diff <fixed-point>...HEAD, and the commit list: git log <fixed-point>..HEAD --oneline.
Confirm the ref resolves (git rev-parse <fixed-point>) and the diff is non-empty before spawning sub-agents. A bad ref or empty diff should fail here, not inside two agents.
2. Find the spec source
In order: (1) a path the caller passed — spec-execution passes the exact spec or ticket file it implemented; use it directly, never refetch over it; (2) issue references in the commit messages (#123, Closes #45) — fetch with gh issue view where available; (3) a spec under docs/specs/ or a ticket under docs/tickets/<slug>/ matching the branch or feature — in no-tracker mode the ticket is the per-PR spec (see ADR 0006); (4) if nothing, ask. If the user says there is no spec, the Spec axis reports "no spec available" and is skipped. (Durable specs/tickets live under docs/, never .scratch/.) The caller-passed path is first because guessing a source that was handed to you is the exact class of error the flow eliminates elsewhere — a commit's Closes #45 must not send the review refetching an issue when spec-execution already gave it the file.
3. Assemble the standards sources
Anything the repo documents about how code should be written — CODING_STANDARDS.md, CONTRIBUTING.md, CLAUDE.md. On top of whatever the repo documents, the Standards axis always carries the smell baseline below, under two rules:
What ships with it
1 file 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.
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.
- 2d ago First seen · 83 lines · 105 tokens per session scan A 2ad8881d7fe7
code-review is a skill published in the GitHub repository assisjp/specflow (17 stars, last pushed 22d ago), licensed MIT. It adds 105 tokens to every session and 1,706 once invoked, about $0.0005 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…