Loading...
Loading...
Found 87 Skills
Remove AI-generated code slop from branches. Use after AI-assisted coding sessions to clean up defensive bloat, unnecessary comments, type casts, and style inconsistencies. Focuses on identifying and removing AI artifacts that degrade code quality.
Provides final code cleanup after task review approval. Removes debug logs, temporary comments, dead code, optimizes imports, and improves readability. Use when asked to clean up code, polish, finalize, tidy up, remove technical debt, or prepare code for completion after review. Not for refactoring logic or fixing bugs—focused solely on cosmetic and hygiene cleanup.
Systematic detection and prioritization of neglected code quality issues: stale TODOs, unused imports, deprecated functions, high complexity, dead code. Use when user requests "code cleanup", "find TODOs", "technical debt scan", or "quality of life fixes". Do NOT use for bug fixing (use systematic-debugging), feature work (use test-driven-development), or formatting-only (use code-linting).
Remove dead code and duplication pragmatically with a 5-phase systematic approach
Repo-wide cleanup of AI-like code noise, behavior-preserving: a comment pass (delete narration, condense bloat, fix stale, keep load-bearing), a read-only audit mode, an opt-in refactor mode for vague names and over-abstraction, a detection mode for dead code and logical inconsistencies, and an execution mode that applies another audit's findings. Use when asked to clean up or condense comments, de-slop vibe-coded files, apply a YAGNI pass, find dead code, apply a slop-audit report, or 'почисти код', 'найди мёртвый код'. Do not use for prose (awesome-humanize-en, awesome-document-style) or for the read-only marker sweep (awesome-slop-audit), whose report it executes.
Post-implementation cleanup of correct code. Prunes comments aggressively: deletes what restates the code, files design rationale to the commit message and wider context to the PR or an issue, collapses one mechanism explained in three places, strips issue and PR references that make a file unreadable on its own, compacts genuine gotchas, renames unclear symbols so a comment is not needed, checks the code against the project's conventions, and simplifies what is more complicated than it needs to be. Tightens docs without gutting them. Auto-applies and reports.
Post-implementation quality check via fresh-eyes review. Chain: Implement → Review (independent agent) → Resolve (if issues). Max 2 rounds. Auto-triggers for security-sensitive and data-mutation code. Not for code refactoring (use code-cleanup). Not for decision analysis (use agent-room). For post-deploy verification, see deploy-verify. For shipping and PRs, see ship.
Read-only audit of a repository for machine-written 'AI slop' across code, comments, tests, docs, configs and CI, against a verified catalog: glyph pockets, stale and false comments, change-narration, drift-bait numbers, template stamps, impossible defensiveness, copy-paste drift, negative-parallelism prose. Every suspect is verified against the code, absence is proven per category, and the ranked findings hand off to awesome-code-cleanup, which owns every edit. Use when asked to find AI slop or machine-written markers, or 'проверь код на следы ИИ'. Do not use to fix what it finds, for prose line-editing (awesome-document-style), or for public-claims drift (awesome-claims-audit).
Read-only whole-project deep audit — architecture and module boundaries, documentation-vs-code fidelity, design-principle adherence (YAGNI/KISS/SOLID), and extensibility (how easily someone builds from source and adds a new provider/plugin/adapter) — producing a prioritized report with a SHIP / FIX / BLOCK verdict. Framework- and language-agnostic. Use when the user asks to 'audit/analyze the architecture', 'review the whole codebase design', 'does the code match the README/docs', 'how hard is it to add a new X', 'is this codebase ready to build on', or 'проведи глубокий анализ проекта', 'оцени архитектуру', 'соответствует ли код документации'. Do not use for a single diff/PR (use awesome-code-review), a named vulnerability (awesome-security-audit), runtime latency/memory (awesome-performance-audit), public-client disclosure (awesome-leak-audit), comment/naming cleanup (awesome-code-cleanup), or design-stage shaping of a new system or API (awesome-design-doc, awesome-api-design).
Universal coding standards — naming, structure, immutability, error handling, type safety, backend layering, frontend architecture — that fill the gaps after the project's own conventions. Use when starting a module, refactoring to team conventions, setting up lint rules, onboarding, or 'стандарты кода'. Do not use for a repo-wide comment cleanup pass (awesome-code-cleanup) or for designing the API error contract (awesome-error-standards).
Restructure code while preserving behavior. Use for extraction, consolidation, ownership moves, or cleanup where verification must bracket structural edits.
Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.