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Pre commit review

Skill moberghr/mtk-agent-toolkit/.claude/skills/pre-commit-review

Fast security-focused review of staged changes before every commit, checking only critical compliance rulesFrom its SKILL.md

Install
npx -y skills add moberghr/mtk-agent-toolkit --skill pre-commit-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

  • 6 stars6 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

9.5 KB, as published. Nobody here has run it

Pre-Commit Security Review

MTK File Resolution

MTK files (hooks/, .claude/references/, .claude/review-config.json) live either in the project (local install) or the plugin cache (marketplace install). Resolve once:

  1. If $MTK_HELPER_ROOT is set, prefix hooks/, .claude/references/, and .claude/review-config.json reads with it — a pinned checkout wins over every other source.
  2. Otherwise, if $CLAUDE_PLUGIN_ROOT is set, prefix them with that.
  3. Otherwise, if hooks/pre-commit-linters.sh exists locally → project-relative paths work as-is.
  4. Otherwise, fall back to find ~/.claude/plugins -maxdepth 8 -name "pre-commit-linters.sh" -path "*/mtk/*" -type f 2>/dev/null | sort -V | tail -1 | sed 's|/hooks/pre-commit-linters.sh||'. If empty, skip the linter pass and run the AI review only.

Run a fast, security-focused review on staged changes only. This is the lightweight check engineers should run before every commit.

Process

  1. Get the staged diff: git diff --cached
  2. If nothing staged, check unstaged: git diff
  3. If nothing at all, tell the engineer there's nothing to review
  4. Run the static linter pass first: bash hooks/pre-commit-linters.sh
    • Emits deterministic findings with source: "linter" and confidence: 100
    • Findings include secrets, raw SQL interpolation, connection strings with plaintext passwords, AWS keys, JWTs, and stack-specific patterns
    • Merge linter findings into your final JSON output (they always pass the threshold, so they always surface) 4.5. Merge cached analyzer output (if available). If .mtk/analyzer-output.json exists and was modified within the last 10 minutes, read it and filter findings to only those whose file field matches a file in git diff --cached --name-only (or git diff --name-only if using unstaged). Discard all other findings — surfacing repo-wide warnings on an unrelated commit erodes trust in the gate. Merge the filtered set into your output with source: "analyzer" and confidence: 100. Do NOT run the build yourself — the pre-commit gate must stay fast (seconds, not minutes). Only consume cached output. 4.6. Roslyn MCP tools (if available, .NET only). If dotnet-claude-kit is installed and the DetectAntiPatterns tool is available, call it on the changed files for on-demand semantic analysis. Treat results as source: "analyzer", confidence: 100. This is fast (analyzes specific files, not full build) and catches EF Core, async, and disposal patterns that the regex linter misses. If the tool is not available, skip this step. 4.6. Collateral-churn check. Run bash hooks/collateral-guard.sh --cached (add --manifest docs/specs/<date>-<slug>.json when this commit belongs to a spec). It answers a question no other check asks: is this churn yours? It flags whitespace/EOL-only rewrites (a small edit to a CRLF file rewrites the whole file), generated artifacts riding along undeclared (one npm install drags a lockfile into a feature commit), and asset directories regenerated wholesale. Findings are warnings, not blocks — but each carries a working revert command, and a commit whose diff is mostly collateral hides the real change from every reviewer downstream. The dependency gate below is the separate, stricter question of what the lockfile churn contains.

4.7. Dependency-introduction gate (if a manifest changed). Detect whether the staged diff touches any of these manifest files: package.json, package-lock.json, pnpm-lock.yaml, yarn.lock, *.csproj, Directory.Packages.props, requirements.txt, pyproject.toml, Pipfile, poetry.lock, go.mod, Cargo.toml, Cargo.lock, Gemfile, Gemfile.lock, composer.json. If any matches, list the newly added dependencies (lines beginning with + introducing a new package name) and walk each through the 5-criteria rubric in .claude/references/dependency-intake-checklist.md — scope, maintenance, size, security, license. Two Poor ratings on a single dep blocks the commit; one Poor requires explicit override in the PR description. Emit each problematic dep as a category: "dependency" finding with source: "ai" and confidence ≥ 85 for Poor ratings backed by evidence (CVE id, last-release date, license SPDX). Pure version bumps within the same major skip the rubric (vulnerability scan only). Skip the gate entirely when the checklist file is absent (older repos). 4.8. Monorepo ripple check. Run bash scripts/monorepo-ripple.sh $(git diff --cached --name-only). On a non-monorepo it exits 0 with no output (no false positives). On a monorepo, each RIPPLE <pkg>: affects <downstream> line becomes a category: "ripple", severity: "warning", source: "linter", confidence: 90 finding. Ripples never block the commit on their own — they exist to make the author aware that staged changes will affect downstream packages. 5. Run the AI review pass on the same diff to catch issues the linter can't reach (design, intent, context-sensitive rules). AI findings use source: "ai" and their own confidence scores per the rubric. 6. Combine linter + AI findings into a single schema-conformant output.

Check ONLY These (from .claude/rules/security.md §1.x and the generated pre-commit-review-list.md (tech-stack items); if neither exists, use the fallback list below):

  • Secrets: Any hardcoded credentials, connection strings with passwords, API keys, tokens?
  • SQL Injection: Any string-concatenated SQL? Must be parameterized only (EF Core is fine — [.NET example]).
  • PII in Logs: Any PII (names, emails, account numbers) in log statements or exception messages?
  • Auth Missing: Any new endpoints without [Authorize] or RequireAuthorization()? [.NET example]
  • Audit Missing: Any state-changing operations on financial data without audit log writes? [finance-domain example]
  • Secrets in Env: Any connection strings or passwords hardcoded in appsettings.json or CDK environment vars? [.NET/AWS example]
  • IAM Blast Radius: Any new IAM grants with * resource that should be scoped? [AWS example]
  • Dependency Intake: New third-party dep added — does it pass the 5-criteria gate in .claude/references/dependency-intake-checklist.md? (Two Poor ratings block.)

COMMON RATIONALIZATIONS — Do Not Fall For These

RationalizationReality
"It's just a DTO change, no security implications"DTOs define what data crosses trust boundaries. A missing [JsonIgnore] on an internal field leaks data. Check it.
"EF Core handles parameterization, so SQL injection isn't possible here"EF Core handles it when you use LINQ. FromSqlRaw with string concatenation is still injection. Check for raw SQL.
"This is an internal endpoint, it doesn't need [Authorize]"Internal endpoints get exposed. Network boundaries shift. Auth on every endpoint. No exceptions.
"The audit trail isn't needed here — this doesn't touch financial data"If it mutates state that affects financial calculations, reports, or compliance records, it needs an audit trail. "Financial data" is broader than you think.
"This change is too small to have security implications"The smallest changes cause the biggest incidents. A one-line config change can expose a connection string. A renamed property can break auth middleware. Check every diff.
"I already reviewed this mentally, running the checklist is redundant"Mental reviews miss things. That's the whole point of a checklist. Pilots don't skip pre-flight because they "already know the plane works."

Output Contract

Emit the schema-conformant output per .claude/references/review-finding-schema.md:

  1. Markdown table of surfaced findings (rows where confidence >= threshold).
  2. Fenced JSON block with the full structured result. If you need extra context fields, stay within the canonical review envelope defined in .claude/references/review-finding-schema.md.

Read .claude/review-config.json for the threshold (default 80; .claude/review-config.local.json overrides if present). Apply the confidence rubric and the anti-inflation rule.

  • Any critical finding at/above threshold → verdict: "NEEDS_CHANGES".
  • Otherwise → verdict: "PASS".
  • If findings[] has fewer than 2 entries, below_threshold_rationale is mandatory — state what you checked and why you conclude the diff is clean.

Keep the table tight. This is a pre-commit gate, not a full review.

Clean pass — compact output

When verdict is PASS and findings[] is empty, skip the table and JSON block entirely. Instead emit a single compact summary:

✅ Pre-commit review passed — 0 findings across 8 rules ({N} files, {A}+/{D}−)

Checked: secrets · SQL injection · PII in logs · auth · audit trail · env secrets · IAM scope · dependency intake

Replace {N}, {A}, {D} with actual file count, additions, and deletions from the diff. This is the only output for a clean pass. No table, no JSON block, no rationale dump.

Findings present — full output

When there are findings (PASS with warnings/suggestions, or NEEDS_CHANGES), emit the standard schema output: markdown table + fenced JSON block per .claude/references/review-finding-schema.md.

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.