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/code-review-pipeline

Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.

From plugin
babysitter
1.8k200 skills3 agents21 commands1 MCP
Install
$ npx -y skills add a5c-ai/babysitter --skill code-review-pipeline --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/code-review-pipeline

Context preview

The summary Claude sees to decide when to auto-load this skill.

Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.

SKILL.md

code-review-pipeline.SKILL.md
name: code-review-pipeline
description: Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.
allowed-tools: Read, Bash, Grep, Glob
graph:
  domains: [domain:software-engineering]
  skillAreas: [skill-area:agentic-loops, skill-area:orchestration-loop]
  workflows: [workflow:feature-development]
  topics: [topic:developer-experience]
  roles: [role:tech-lead, role:backend-engineer]
  • Logic errors and off-by-one mistakes
  • Edge case handling (null, undefined, empty, boundary)
  • Type safety (no implicit any, proper narrowing)
  • Error handling completeness
  • Floating promise detection
  • Race condition analysis

Dimension 2: Security

  • Injection vectors (SQL, XSS, command, template)
  • Authentication and authorization gaps
  • Data exposure (PII, credentials, internal state)
  • Dependency vulnerabilities (known CVEs)
  • Input validation completeness

Dimension 3: Performance

  • Algorithmic complexity (O(n^2) detection)
  • Memory leaks (event listeners, closures, caches)
  • Unnecessary allocations in hot paths
  • Database query optimization (N+1, missing indexes)
  • Bundle size impact

Dimension 4: Maintainability

  • Naming clarity and consistency
  • Documentation completeness (JSDoc, inline comments)
  • Test coverage adequacy
  • Coupling analysis (afferent/efferent)
  • File organization compliance

Confidence Gating

  • Score each issue 0-100 on confidence
  • Only report issues >= 80% confidence
  • Prevents false positive noise
  • Higher confidence for clear patterns, lower for heuristic matches

Remediation Loop

  • Prioritize: critical > high > medium > low
  • Apply fixes via refactor-cleaner agent
  • Re-review after remediation
  • Maximum 2 remediation cycles
  • Exit when no critical/high issues remain

When to Use

  • Post-implementation review
  • Pre-merge PR review
  • Security audit
  • Technical debt assessment

Agents Used

  • `code-reviewer` (primary)
  • `refactor-cleaner` (remediation)
Read more
Ships withbabysitter

Enforce obedience on agentic workforces. Manage extremely complex workflows through deterministic, hallucination-free self-orchestration.

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