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概要と使いどころ
Deep competitive analysis for iOS/macOS apps including feature comparison, pricing analysis, strengths/weaknesses, market positioning, and differentiation opportunities. Use when user asks for competitive analysis, competitor research, feature comparison, market positioning, or wants to understand competition in detail.
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。
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
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。
Run Semgrep static analysis across a codebase, optionally using Semgrep Pro for cross-file taint analysis. Use when Semgrep or a static-analysis scan is requested; use security-review for a manual audit.
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。
Provides file paths to language-specific reference files for the test ANALYSIS skills (assertion-quality, test-anti-patterns, test-gap-analysis, test-smell-detection, test-tagging). Read this catalog to discover available extension files (e.g., dotnet.md for .NET/MSTest/xUnit/NUnit/TUnit, python.md for pytest/unittest, typescript.md for Jest/Vitest/Mocha, java.md for JUnit/TestNG, etc.). Do not invoke this reference-only skill — its bundled files are read by the quality agent and analysis skills needing framework-specific lookup tables (test markers, assertion APIs, skip annotations, sleep patterns, mystery guest indicators, integration markers, setup/teardown, tag-support capability).
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。
Audit a test file or suite; produce a severity-ranked diagnostic report. ALWAYS USE for tests that verify nothing, missing/tautological assertions, swallowed/broad exceptions, flaky/order-dependent tests, duplication, or magic values. Polyglot. DO NOT USE for direct edits: writing-mstest-tests owns supplied MSTest assertions/attributes/lifecycle; code-testing owns new tests. Exclude running tests, migration, assertion metrics (assertion-quality), raw .NET coverage collection (run-tests), non-.NET coverage collection/analysis (native tooling), project-wide .NET coverage/CRAP (coverage-analysis), named-target .NET CRAP (crap-score), behavioral/pseudo-mutation gaps (test-gap-analysis), test-mix/ happy-vs-error classification and trait distributions (test-tagging), or the testsmells.org catalog (test-smell-detection).
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。
Activation requires either supplied .NET coverage reports/percentages/line, branch, or condition metrics, or an explicit request to collect .NET coverage for analysis. USE FOR: interpreting that evidence, including Cobertura data, partial conditions, plateaus, target arithmetic, project-wide coverage-backed CRAP, and coverage-backed refactoring safety. Analyze supplied reports directly without rerunning tests or installing tools. DO NOT USE FOR: requests with neither coverage evidence nor explicit coverage-collection intent, including hypothetical change-survival questions (use test-gap-analysis); CRAP or refactoring safety for one named target (use crap-score); or requests owned by test-tagging, find-untested-sources, test-anti-patterns, run-tests, or code-testing.
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。
Static and dynamic malware analysis, YARA rule generation, sandbox configuration, behavioral profiling, and malware family classification
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。
Entry point + orchestrator for the recomby-geo GEO (Generative Engine Optimization) workflow on OpenAI Codex CLI. Use when the user wants to run any stage of the GEO pipeline on a client folder — intake, visibility audit, content-gap analysis, content brief, draft production, distribution, or monthly re-audit — or asks to "run GEO", "audit AI search visibility", or "GEO this client". Codex has no bare slash commands, so this skill is how the 7 stages (that Claude Code runs as /01-intake … /07-reaudit) are driven on Codex. It routes to the per-stage specs in this plugin's commands/ and enforces the orchestration rules. Does not auto-fill expert content — the human-in-loop brief checkpoint is the moat.
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。
Use code-review-graph for local-first CLI/MCP code knowledge graphs, graph-backed code review, structural search, and repository-analysis integrations.
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。
Evidence-based investigation of issues, bugs, API calls, integrations, and other aspects of software development that need a deep dive to find the root cause and solutions. Use when you need to debug, troubleshoot, diagnose, or figure out why something is broken. Does not review code for quality or style — use code-review for auditing changes or post-code-review-to-pr for posting review feedback to GitHub. Does not assess architectural health or structural risk — use architectural-analysis for architectural concerns. Does not research open-ended options, prior art, or how something works when nothing is broken — use research for that. Does not plan the structural change a root cause calls for — use plan-a-change. Does not map bounded contexts or domain boundaries — use ddd-analysis. Does not capture feedback on Han's own skills — use han-feedback for that.
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。
Verify code correctness statically against specifications using type checking, contract verification, and formal methods. Use when: (1) Verifying type safety and null safety in Python, Java, or C/C++ code, (2) Checking design-by-contract specifications (preconditions, postconditions, invariants), (3) Validating code against formal specifications, (4) Ensuring code quality and correctness before runtime, (5) Finding potential bugs through static analysis. Supports Python (mypy, contracts), Java (javac, JML), and provides verification scripts and contract specification guidelines.
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。
WordPress performance code review and optimization analysis. Use when reviewing WordPress PHP code for performance issues, auditing themes/plugins for scalability, optimizing WP_Query, analyzing caching strategies, checking code before launch, or detecting anti-patterns, or when user mentions "performance review", "optimization audit", "slow WordPress", "slow queries", "high-traffic", "scale WordPress", "code review", "timeout", "500 error", "out of memory", or "site won't load". Detects anti-patterns in database queries, hooks, object caching, AJAX, and template loading.
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。
AI-powered Claude Code skill that performs deep code review using formal logic and reasoning frameworks to detect bugs, anti-patterns, and security risks beyond what linters catch.
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。
Vulnerability audit and dataflow analysis built on the neug CPG engine. file_audit (default, recommended): first builds a function-level summary graph (tier1) over the entire project, then incrementally builds detailed CPGs (tier2) on demand for chosen functions; both tiers coexist in a single neug database (unified schema, cross-layer refines edges; C/Java/Python/Rust). All capabilities are exposed as CLI tool subcommands (audit/overview/build/query/methods/paths), so an agent can drive the audit step by step via shell; the audit subcommand can also run the built-in LLM loop. The same tooling also supports a dataflow analysis mode (Workflow C): no vulnerability hunting, only variable-level dataflow tracing for functions of interest, producing dataflow_analysis.json. repo_audit: multi-round LLM/Cypher audit over a full-repo CPG. Use when the user asks to audit a codebase/project for vulnerabilities, scan a project with CPG/neug, run repo_audit/file_audit, find source-to-sink taint paths, or analyze dataflow inside a function. Supports C, Java, Python, and Rust.
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。
Full SEO toolkit for Claude Code, powered by the DataForSEO API. Replaces the data layer of an SEO agency: keyword research, competitor analysis, rank tracking, backlink audits, technical site crawls, content gap analysis, and client-ready PDF reports — all with real Google search data, not scraping. Use when the user says "seo", "keyword research", "rank check", "backlinks", "competitor analysis", "site audit", "content gap", "compare domains", or passes a domain / URL / keyword for SEO analysis.
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。
GitHub 解封 — 账号封禁/限制/恢复的领域操作系统。覆盖：(a) GitHub 官方政策体系 (TOS / 可接受使用政策 / Trust & Safety 执行模式 / 公开申诉路径 / 受制裁地区解读)；(b) 封号原因诊断学 (spam / abuse / 制裁误标 / 2FA 丢失 / ToS 违规 / 账号劫持误判 / ban evasion 等子类型 + 症状→原因映射 + 自我分诊压测)；(c) 申诉实操 craft (写一封能让 T&S 快速判误伤的英文申诉信 + 升级阶梯 + 法务介入边界 + Don'ts)；(d) 制裁与合规硬边界 (OFAC SDN 名单 / 哪些国家或地区真不可达 / VPN 误判路径 / 中国大陆不是美国制裁地区的反复重申)；(e) 中国大陆开发者特别处境 (sanctioned region 误标 + SMS 验证不支持 +86/+852 + Gitee/GitLab/Codeberg/JihuLab 备用迁移 + 私有自托管 Gitea/Forgejo)；(f) 真实案例库 (~30+ 公开案例分类拆解：误伤 / 真违规 / 制裁误标三类各自赔率与申诉成功路径)。伦理锚绝不软化：不教 ban evasion / 不教撒谎式申诉 / 真违规承认改进 / 丢 2FA 无恢复因子则诚实告知 / 中国制裁误标靠申诉不靠换 VPN / 申诉 6 个月窗口必算清 / 约 3% (业内估) 真违规恢复 vs 约 79% (业内估) 误伤申诉成功率分层标。 (GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: false-positive / genuine violation / sanctions mis-flag, each with win-rate and appeal success path). Ethical anchors absolutely not softened: do NOT teach ban evasion (creating new accounts turns a temp ban into a permanent one — the single biggest mistake); do NOT teach social engineering or lying in appeals (misuse + actually confirms violation); genuine violations: admit + improve beats denial; lost 2FA + no recovery factor → do not pretend recovery is possible; China sanctioned-region mis-flag → fix via appeal, not repeated VPN switching; appeal form 6-month window must be counted carefully; historical 约 3% (业内估) genuine-violation recovery vs 约 79% (业内估) false-positive appeal success rate stratification must be honestly labeled. Anti-samples (explicitly describe harm, never endorse): developer permabanned for ban evasion / open-source team org-banned for personal attacks in public issues / cases where repeated VPN switching escalated risk-control severity.) Master OS — automated mastery of GitHub Account Reinstatement — the domain operating system for GitHub (and analogous platform) account suspension, restriction, appeal, and recovery. Covers: (a) GitHub official policy architecture (TOS / Acceptable Use Policies / Trust & Safety enforcement patterns / public appeals pathways / sanctioned-region interpretation); (b) suspension-cause diagnostics (spam / abuse / sanctions mis-flag / 2FA loss / ToS violation / account hijack false-positive / ban evasion taxonomy + symptom→cause mapping + self-triage pressure test); (c) appeal craft (writing an English appeal letter that gets T&S to fast-track a false-positive ruling + escalation ladder + legal-engagement boundary + Don'ts); (d) sanctions and compliance hard boundaries (OFAC SDN list / which countries/regions are truly unreachable / VPN false-positive paths / China is NOT a US-sanctioned region — repeated emphasis); (e) mainland China developer special circumstances (sanctioned-region mis-flag + SMS verification does not support +86/+852 + Gitee/GitLab/Codeberg/JihuLab fallback migration + self-hosted Gitea/Forgejo); (f) real-case library (~30+ public cases with categorized analysis: fa
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。
Apply semi-formal certificate reasoning to code analysis — patch verification, fault localization, patch equivalence. Use when reviewing patches, hunting bugs across scopes, comparing fixes, or when code reasoning requires tracing execution across files/modules. Triggers on code review, bug localization, patch comparison, name shadowing, scope analysis, regression checking.
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。
Index a code repository into Cognee's code graph and query it deterministically (callers, impact analysis, paths, endpoints). Use for structural code questions, "index this repo", and checking what a re-index changed.
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。
Use when indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Codex.
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。
🇺🇸 User Interview & Cold-Start Operations Playbook — Battle-tested framework from HeyGen's 937 interviews to PMF. Complete SOP for user screening, interview execution, Beta testing methodology, cold-start user operations, churn analysis, and user grading systems. 🇨🇳 用户访谈与冷启动运营实战手册 — 基于 HeyGen 937 场访谈验证的 PMF 方法论。包含用户筛选、访谈执行、Beta 测试设计、冷启动用户运营、流失分析、用户分级体系完整 SOP。 🇯🇵 ユーザーインタビュー＆コールドスタート運営プレイブック — HeyGenの937回インタビューで検証されたPMF方法論。ユーザースクリーニング、インタビュー実行、Betaテスト設計、コールドスタートユーザー運営、離脱分析、ユーザーグレーディング。 🇰🇷 사용자 인터뷰 & 콜드 스타트 운영 플레이북 — HeyGen 937회 인터뷰로 검증된 PMF 방법론. 사용자 스크리닝, 인터뷰 실행, Beta 테스트 설계, 콜드 스타트 사용자 운영, 이탈 분석, 사용자 등급 시스템. Triggers: "user interview" | "user research" | "customer discovery" | "PMF" | "product-market fit" | "beta test" | "beta testing" | "cold start users" | "cold start operations" | "churn analysis" | "user grading" | "用户访谈" | "用户调研" | "冷启动" | "冷启动运营" | "Beta测试" | "流失分析" | "用户分级"
Analyze git repository history to produce a codebase risk profile before code review. Probes repo size, runs 7 parallel git analysis pipelines (hotspots, bug magnets, bus factor, contributor momentum, firefighting frequency, newly added files), cross-references hotspots with bug magnets to identify high-risk files with primary owner annotation, and writes walkthrough/recon-report.md. Use before code review to prioritize reviewer attention, at the start of linear-walkthrough Phase 1 Discovery to weight file coverage, or when onboarding to an unfamiliar 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。
Cross-verify Claude-generated plans and code using OpenAI Codex and Google Gemini CLI. Provides code review, plan validation, and comparative analysis. Use when needing second opinions on Claude's code or plans, validating technical decisions, or seeking consensus from multiple AI models.
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。
Build and query architecture-aware code search, dependency graphs, call flows, impact analysis, and belief maps for Python, TypeScript, TSX, Rust, C#, Java, Go, Ruby, and Ruby on Rails repositories. Use before non-trivial code changes to find module boundaries, blast radius, architecture violations, and the minimal source files to read.
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。
Shell out to OpenAI Codex CLI for headless code generation, analysis, and question-answering. Optimized for code tasks. Requires OPENAI_API_KEY env var.
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。