agentsclimarketplace

Review

Skill Brayanhenaor/ai-standards/skills/review

Audit code against the full Supercode ruleset and report real problems and clean-code improvements by severity. Use when asked to review code, audit a change, check quality before a PR, or find clean-code issues. Scope is the current diff (default) or the whole project.From its SKILL.md

Install
npx -y skills add Brayanhenaor/ai-standards --skill review

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.7 KB, as published. Nobody here has run it

Review

Audit code against the whole Supercode ruleset — clean-code-core, anti-overengineering, and the active stack pack (e.g. .NET) — and report real findings, not nitpicks. The heavy, isolated work runs in the code-reviewer subagent; this skill picks the scope, dispatches, and consolidates.

Usage

/supercode:review            # default: the current diff (uncommitted changes vs HEAD)
/supercode:review --diff     # explicit diff scope
/supercode:review --full     # the whole project (or a path: --full src/payments)

1. Resolve scope

  • --diff (default): the working changes. Collect them with:
    • git diff --name-only HEAD (staged + unstaged)
    • git ls-files --others --exclude-standard (new untracked files)
    • If the tree is clean, tell the developer there's nothing to review and offer --full.
  • --full: all source files under the repo root, or under the given path. Respect .gitignore; skip vendored/generated/build dirs (node_modules, bin, obj, dist, .git). For a large tree, review by module and state what you covered and what you deferred — never imply full coverage you didn't do.

2. Detect the active stack

Identify the language/stack from the files and project markers (*.csproj, package.json, pyproject.toml, go.mod…). If a Supercode stack pack matches, the reviewer applies its rules on top of the core. If none matches, the universal core still fully applies.

3. Dispatch the reviewer

Launch the code-reviewer subagent with the resolved file set and stack. For a large --full run, split by module and launch reviewers in parallel, one per module. Pass each the exact files to read so it doesn't wander the whole tree.

4. Consolidate and report

Merge the subagent findings, drop duplicates, and present grouped by severity, highest first:

[CRITICAL]    file:line — problem · why it matters · suggested fix
[IMPROVEMENT]  file:line — problem · why · suggested fix
[TECHNICAL]   file:line — problem · why · suggested fix
  • Lead with a one-line verdict (e.g. "3 critical, 7 improvements across 12 files").
  • Report only findings you can justify against a rule — no style preferences dressed up as defects.
  • Do not edit code here; review reports, it doesn't fix. (A fix pass is a separate, explicit step.)
  • Reply in the developer's language; keep code, identifiers, and snippets in English.

Keep looking

Skills are one crate of 627,801. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.