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Found 137 Skills
Audit, score, and improve any project's Claude Code configuration. Analyzes CLAUDE.md, skills, agents, hooks, MCP servers, and settings. Trigger: /refine, /refine audit, /refine quick
Captures quality metrics baseline (tests, coverage, type errors, linting, dead code) by running quality gates and storing results in memory for regression detection. Use at feature start, before refactor work, or after major changes to establish baseline. Triggers on "capture baseline", "establish baseline", or PROACTIVELY at start of any feature/refactor work. Works with pytest output, pyright errors, ruff warnings, vulture results, and memory MCP server for baseline storage.
Comprehensive code investigation and audit tool. Discovers all project features, then dispatches parallel subagents to analyze issues, risks, dead code, missing functionality, and redundancies. Produces a prioritized risk report. Use this skill when the user asks to "investigate code", "audit project", "find risks", "check code quality", "analyze codebase", "what's wrong with this code", "project health check", "code review entire project", "find dead code", "find redundant code", or any request for a thorough codebase analysis.
Audit and optimize Claude Code configuration with dynamic best-practice research
Gold-standard code review for SAP CC Go repositories against the project's lead review standards. Dispatches 10 domain-specialist agents in parallel — each loads domain-specific references and scans ALL packages for violations in their assigned domain. Produces a prioritized report with REJECTED/CORRECT code examples. Optional --fix mode applies corrections on a worktree branch. This is the definitive "would this code pass lead review?" assessment.
Audits code for design pattern opportunities and anti-patterns — identifies places where a specific GoF or architectural pattern would solve an observable problem, and flags misapplied patterns that add complexity without benefit. Generates fix prompts. Trigger phrases: "design patterns", "pattern check", "pattern review", "refactoring patterns", "pattern analysis".
Run a full Flows app platform review against a React/TypeScript CDF codebase, following the cognitedata/dune-app-reviews scoring criteria. Produces three artifacts: review-files.md (per-file inventory), review-packages.md (dependency audit), and review-report.md (scored report with must/should/nice-fix items). Use when the user asks for a Flows app review, pre-submit review, approval review, app certification review, code quality audit, CDF platform review, or "run dune-review" on a codebase before submission.
Audit a design proposal or diff against Exarchos's architectural invariants — event-sourcing integrity (INV-1), facade equivalence over shared dispatch core (INV-2), basileus-forward (INV-3), platform-agnosticity (INV-4), and agent-first interface design (INV-5a input ergonomics, INV-5b spec-aligned output contract, INV-5c Aspire-inspired control-plane verbs, INV-5d action discriminator pattern). Pairs with /axiom:backend-quality — this skill is project-specific (axiom is generic). Triggers: 'check invariants', 'design conformance', 'check #1118 / #1109', or /design-invariants.
Use when inspecting, cleaning, understanding, reproducing, or auditing academic research code repositories, especially when README commands, datasets, checkpoints, experiments, or paper claims need verification.
Security vulnerability detection and variant analysis skill. Use when hunting for dangerous APIs, footgun patterns, error-prone configurations, and vulnerability variants across codebases. Combines sharp edges detection with variant hunting methodology.
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or the loop cap is reached. Use when: implementing features from a spec or plan, hardening existing code, fixing a batch of issues, or any multi-file task that benefits from a build-verify-fix cycle.
Write and audit Python code comments using antirez's 9-type taxonomy. Two modes - write (add/improve comments in code) and audit (classify and assess existing comments with structured report). Use when users request comment improvements, docstring additions, comment quality reviews, or documentation audits. Applies systematic comment classification with Python-specific mapping (docstrings, inline comments, type hints).