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/hitmandark07/neatcodeai/code-reviewnpx skills add HITMANdark07/neatcodeai --skill code-reviewgit clone --depth 1 https://github.com/HITMANdark07/neatcodeaiWhat 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 | $0.00065 | $0.01636 |
| Opus 5 | $0.00032 | $0.00818 |
| Sonnet 5 | $0.00013 | $0.00327 |
| Haiku 4.5 | $0.00006 | $0.00164 |
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 yesterday.
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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Overview
Catch issues before they cascade. A review pass has three jobs:
- Confirm the captured rules pass. Run
validate_diffagainst the changes; rule violations are non-negotiable Critical issues. - Read the diff with fresh eyes. Look for dead code, missing tests, half-finished implementations, error-handling gaps, security smells, and assumptions that aren't justified by the change.
- Verify intent matches outcome. The diff should accomplish exactly what the task or PR description claims — no more, no less.
Output is a structured report the user can act on.
When to call
Mandatory:
- After finishing a task in a multi-task plan, before moving to the next task.
- Before telling the user a feature is done.
- Before commit / before merge to main.
Optional but valuable:
- When stuck — fresh perspective on the diff often surfaces the issue.
- After fixing a complex bug, before claiming it's fixed.
- Before a refactor — baseline check on what currently works.
Skip when:
- Single-character typo fix.
- The user is the one reviewing in real time and explicitly didn't ask.
Procedure
Step 1: Define the scope
Identify exactly what's being reviewed:
# For uncommitted changes:
git status
git diff --stat
# For a branch:
BASE=$(git merge-base origin/main HEAD)
git diff --stat $BASE..HEAD
# For a single commit:
git show --stat <sha>
Capture: list of changed files, total lines added/removed, the task description or PR title.
Step 2: Run rule validation
Call validate_diff with the changed files and their final contents. Any violation here is a Critical issue — the change is conceptually wrong by the team's own captured rules.
validate_diff({
changes: [
{ path: "<repo-relative>", content: "<full final content>" },
...
]
})
If the diff is committed already, run validate_diff with the on-disk content (still works — the engine treats it as a virtual graph).
Step 3: Read the diff for non-rule issues
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.
- yesterday First seen · 175 lines · 65 tokens per session scan A 4a8210a0fe9e
code-review is a skill published in the GitHub repository HITMANdark07/neatcodeai (0 stars, last pushed 3mo ago), licensed MIT. It adds 65 tokens to every session and 1,636 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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-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…