in-the-loop-labs/ai-critic
plugin/skills/ai-critic/SKILL.md
Fetch AI-generated review suggestions from pair-review and make code changes to address them. Use when the user says "address AI feedback", "address AI suggestions", "fix AI review feedback", or wants to iterate on code based on AI analysis results from pair-review.
$ install --global
skillsauthnpx skillsauth add in-the-loop-labs/pair-review ai-criticInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 20, 2026, 7:06 AM17.4s1 file scanned
SKILL.md
- name:
- ai-critic
- description:
- >
AI Critic
Fetch AI-generated suggestions from pair-review and make code changes to address the valid ones.
Determine review context
Determine whether this is a local review or a PR review:
- If the user explicitly says "local", use local mode.
- Otherwise, determine the GitHub owner, repo, and PR number for the current branch. If a PR exists, use PR mode with
repoandprNumberparams. - If no PR exists, use local mode with
path(absolute cwd) andheadSha(git rev-parse HEAD) params.
Fetch AI suggestions
Call mcp__pair-review__get_ai_suggestions with the review context params. This returns suggestions from the latest analysis run by default.
If the user wants suggestions from a specific analysis run, call mcp__pair-review__get_ai_analysis_runs first to list available runs, then pass the appropriate runId to get_ai_suggestions.
Only active and adopted suggestions are included (dismissed ones are excluded).
If no suggestions are returned, tell the user there are no AI suggestions to address.
Triage and address suggestions
AI suggestions are not human-curated — apply judgment. For each suggestion:
- Read the file at the referenced path and lines.
- Evaluate the suggestion: is it a real issue, a false positive, or a stylistic preference?
- If the suggestion is valid and actionable, make the code change.
- If the suggestion is a false positive or not worth addressing, skip it and note why.
Use the ai_confidence field as a signal but not a hard threshold — low-confidence suggestions can still be valid.
Report
After processing all suggestions, provide a summary:
- How many suggestions were reviewed
- Which ones were addressed (and what changed)
- Which ones were skipped (and why)
Related Skills
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Open outstanding GitHub review requests in pair-review for AI-powered code review. Finds open PRs where my review is pending from the past week and starts pair-review analysis for each. Use when the user says "review requests", "review my PRs", "check review requests", "open review requests", "pair-review my requests", or wants to batch-review their outstanding GitHub review requests.
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in-the-loop-labs/pr
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Open the GitHub pull request for the current branch in the pair-review web UI. This only opens the browser — it does not run AI analysis or generate suggestions. Once open, the user can browse the diff, leave comments, and trigger analysis from the web UI themselves. Use when the user says "review this PR", "review pull request", "open PR review", or wants to open a pair-review session for the current branch's pull request. If the user wants automated AI analysis of the PR rather than just opening the browser, use the `code-critic:analyze` skill (standalone, requires code-critic plugin) or `pair-review:analyze` skill (requires MCP server) instead. Note that the user can also trigger AI analysis from within the pair-review web UI after opening it.
28SKILL.mdUpdated Apr 20, 2026
in-the-loop-labs/local
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Open local uncommitted changes for review in the pair-review web UI. This only opens the browser — it does not run AI analysis or generate suggestions. Once open, the user can browse the diff, leave comments, and trigger analysis from the web UI themselves. Use when the user says "review my local changes", "review local", "open local review", or wants to open a pair-review session for uncommitted work in the current directory. If the user wants automated AI analysis of their local changes rather than just opening the browser, use the `code-critic:analyze` skill (standalone, requires code-critic plugin) or `pair-review:analyze` skill (requires MCP server) instead. Note that the user can also trigger AI analysis from within the pair-review web UI after opening it.
28SKILL.mdUpdated Apr 20, 2026