techdebt
無料Analyze Elixir/Phoenix technical debt — duplicates, refactoring opportunities, credo issues. Use when asked about code quality, cleanup, or what to improve.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Analyze Elixir/Phoenix technical debt — duplicates, refactoring opportunities, credo issues. Use when asked about code quality, cleanup, or what to improve.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze Phoenix context boundaries and module coupling via mix xref. Use when checking cross-context calls, validating dependencies, before splitting modules, or reviewing architecture.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze skill effectiveness across sessions. Computes per-skill metrics (action rate, friction, outcomes), identifies degrading skills, and generates improvement recommendations. Requires session-scan data in metrics.jsonl.
日本語の概要は準備中です。原文の説明を表示しています。
CONTRIBUTOR TOOL - Track CC changelog, extract new versions since last check, analyze impact on plugin (breaking changes, opportunities, deprecations). Run periodically or before releases. NOT part of the distributed plugin.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze trends across session metrics. Computes windowed aggregates, deltas, and compares against MEMORY.md findings. Use periodically for progress tracking.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes a codebase's modularity imbalances using the Balanced Coupling model and produces a review of design issues. Use when reviewing existing code for coupling problems, assessing architecture quality, identifying distributed monolith risks, or finding areas where changes are unexpectedly expensive.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes album state and recommends the optimal next action. Use when the user asks "what should I do next?" or "what's left to do?"
日本語の概要は準備中です。原文の説明を表示しています。
A complete marketing department in one skill. Website and landing-page audits with weighted 0-100 scores, copywriting with panel scoring and AI-slop removal, an 18-tactic ad hook engine, GEO/AEO for getting cited by ChatGPT/Perplexity/AI Overviews, paid-ads creative diagnosis and production briefs, email sequences, LinkedIn/X writing, launch playbooks, positioning and offer design, competitor teardowns, app store optimization, honest analytics and test design. Use for ANY marketing task — audit, write, rewrite, diagnose, score, plan, launch, position, price, analyze — whenever the user mentions marketing, growth, conversion, copy, ads, hooks, CPM, ROAS, SEO, GEO, email, social, landing pages, funnels, launches, competitors, brand, positioning, pricing, or app stores, or says "my landing page sucks", "nobody's converting", "why are my CPMs up", "AI doesn't recommend us", "write me 20 hooks". Route via the table inside; fan out subagents for multi-dimensional work. Not for pure engineering, legal, or finance.
日本語の概要は準備中です。原文の説明を表示しています。
Address PR review feedback by systematically working through every unresolved PR review thread on the current branch's PR - analyze each comment, make the requested code changes (with tests where useful), commit, and optionally reply and resolve.
日本語の概要は準備中です。原文の説明を表示しています。
拼写变体标准化工具。统一英美拼写差异(colour→color、analyse→analyze 等),内置 153 词条 (含屈折形式 covered/covering 等),支持自定义词典扩展。当用户提到英美拼写统一、拼写变体、 British/American spelling 等需求时使用此skill。
日本語の概要は準備中です。原文の説明を表示しています。
Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".
日本語の概要は準備中です。原文の説明を表示しています。
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes recent CI failures on pull requests to identify flaky tests, using retry outcomes (failed attempt → green re-run) and cross-PR recurrence as evidence, and maintains a local longitudinal ledger so flakiness can be tracked over time. TRIGGER when: the user wants to find flaky tests, correlate recent CI failures, check which tests fail across PRs or recover on retry, or refresh the flakiness trend report. DO NOT TRIGGER when: babysitting a single PR's CI until green → monitoring-pull-requests; diagnosing or fixing one specific failing test → the bug-analysis skills.
日本語の概要は準備中です。原文の説明を表示しています。
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze repository structure, patterns, conventions, and documentation for understanding a new codebase
日本語の概要は準備中です。原文の説明を表示しています。
Code refactoring workflow - analyze → plan → implement → review → validate
日本語の概要は準備中です。原文の説明を表示しています。
Analyze brownfield codebase and create initial continuity ledger
日本語の概要は準備中です。原文の説明を表示しています。
Migration workflow - research → analyze → plan → implement → review
日本語の概要は準備中です。原文の説明を表示しています。
Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
日本語の概要は準備中です。原文の説明を表示しています。
Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.
日本語の概要は準備中です。原文の説明を表示しています。
Conduct comprehensive AI-powered research with citations via the Tavily CLI. Use this skill when the user wants deep research, a detailed report, a comparison, market analysis, literature review, or says "research", "investigate", "analyze in depth", "compare X vs Y", "what does the market look like for", or needs multi-source synthesis with explicit citations. Returns a structured report grounded in web sources. Takes 30-120 seconds. For quick fact-finding, use tavily-search instead.
日本語の概要は準備中です。原文の説明を表示しています。
Configure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.
日本語の概要は準備中です。原文の説明を表示しています。