Analyzes a repository and its test suite to generate customized mutation operators tailored to the project. Use this skill when setting up mutation testing, improving test quality, or generating project-specific mutants. Considers language constructs, business logic patterns, API calls, data types, and code complexity to produce effective mutation operators that maximize test sensitivity while avoiding trivial or equivalent mutations. Generates prioritized operator sets (high/medium/low value) with impact summaries. Triggers when users ask to generate mutation operators, customize mutation testing, analyze code for mutation opportunities, or create project-specific mutants.
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。
ArabelaTso/Skills-4-SE☆ 2552026年8月21日 更新
Extract programming-language-agnostic pseudocode from source code in any language, preserving control flow and logical structure while filtering out implementation details. Use when the user asks to convert code to pseudocode, abstract code logic, understand code structure without syntax, create language-independent documentation, or analyze algorithmic flow without language-specific details.
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。
ArabelaTso/Skills-4-SE☆ 2552026年8月21日 更新
Generate comprehensive test scenarios, user stories, and acceptance criteria from requirements and specifications. Use this skill when planning testing efforts, writing user stories, creating test cases, documenting acceptance criteria, exploring edge cases, designing test coverage, or translating requirements into actionable scenarios. Supports BDD (Given-When-Then), Gherkin syntax, user story format, and test case documentation.
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。
ArabelaTso/Skills-4-SE☆ 2552026年8月21日 更新
Explains runtime errors and compilation failures with actionable debugging guidance. Use when Python or Java code throws runtime exceptions (NullPointerException, TypeError, AttributeError, etc.), compilation errors (syntax errors, type mismatches, import failures), or dependency issues. Analyzes error messages, stack traces, and code context to identify root causes and provide concrete fixes with examples. Distinct from test-related errors - focuses on errors during normal code execution and build 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。
ArabelaTso/Skills-4-SE☆ 2552026年8月21日 更新
Guidance for composing well-formatted, effective Slack messages using mrkdwn syntax
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。
w95/awesome-claude-corporate-skills☆ 2542026年2月27日 更新
Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.
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。
w95/awesome-claude-corporate-skills☆ 2542026年2月27日 更新
Automatically organizes invoices and receipts for tax preparation by reading messy files, extracting key information, renaming them consistently, and sorting them into logical folders. Turns hours of manual bookkeeping into minutes of automated organization.
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。
w95/awesome-claude-corporate-skills☆ 2542026年2月27日 更新
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
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。
w95/awesome-claude-corporate-skills☆ 2542026年2月27日 更新
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
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。
w95/awesome-claude-corporate-skills☆ 2542026年2月27日 更新
Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.
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。
skillmds/skillmd☆ 2462026年10月14日 更新
Overlay doctrine for the embedded-captions workflow — the caption MODEL (drop / rail / embed) and the rule that captions are an OVERLAY composited on top of the film, never a reserved bottom band you shift content up to avoid. Load when adding captions/subtitles to a talking-head or launch video, when deciding whether a phrase should be dropped, ride the verbatim rail, or be promoted to a scarce embedded climax, when laying out a composition that will carry captions (do NOT reserve a keep-out band), or when centering a composition on the true frame center under captions. Quotes the rail+embed model from embedded-captions and constraint
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。
skillmds/skillmd☆ 2462026年10月14日 更新
An enterprise-infrastructure marketing canvas built around a near-black ground (#000000) and a system of per-product accent colors — Terraform purple, Vault yellow, Consul pink, Waypoint cyan, Vagrant blue — that act as identity tokens rather than decorative palette. Display type is hashicorpSans set in 600/700 with tight 1.17–1.21 line-heights; body type runs the same family at 500 weight with relaxed 1.50–1.71 line-heights. Cards live as charcoal surfaces with 1px translucent gray borders; product showcase cards lift into per-product chromatic gradients. The system reads as confident, technical, and intentionally multi-product — every section quietly signals which HashiCorp tool it represents.
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。
skillmds/skillmd☆ 2462026年10月14日 更新
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。
elvismdev/claude-wordpress-skills☆ 2352025年11月29日 更新
GitHub repository automation (CI/CD, issue templates, Dependabot, CodeQL). Use for project setup, Actions workflows, security scanning, or encountering YAML syntax, workflow configuration, template structure errors.
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。
secondsky/claude-skills☆ 2302026年9月28日 更新
100+ animated React components (Aceternity UI) for Next.js with Tailwind. Use for hero sections, parallax, 3D effects, or encountering animation, shadcn CLI integration errors.
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。
secondsky/claude-skills☆ 2302026年9月28日 更新
Use for bun:test syntax, assertions, describe/it, test.skip/only/each, and basic patterns.
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。
secondsky/claude-skills☆ 2302026年9月28日 更新
Classify expenses by category, department, and tax deductibility from transaction data. Use when the user requests expense categorization or provides relevant inputs for this workflow.
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。
seb1n/awesome-ai-agent-skills☆ 2172026年8月10日 更新
Optimize a webpage for search engines by analyzing on-page elements, improving technical performance, and implementing structured data for maximum visibility. Use when the user requests seo optimization or provides relevant inputs for this workflow.
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。
seb1n/awesome-ai-agent-skills☆ 2172026年8月10日 更新
Optimize machine learning model hyperparameters using grid search, random search, Bayesian optimization, and Hyperband to maximize model performance within a compute budget. Use when the user requests hyperparameter tuning or provides relevant inputs for this workflow.
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。
seb1n/awesome-ai-agent-skills☆ 2172026年8月10日 更新
Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.
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。
inference-gateway/inference-gateway☆ 2152026年10月16日 更新
Think and work like an expert Microbial Physiologist. Use when a task calls for Microbial Physiologist judgment. Reasons from Monod/chemostat (μ = D), YX/S and Pirt maintenance, Crabtree/overflow, 13C-MFA and FBA, and BMSAB taxonomy; treats OD-as-biomass yield error, FBA-as-measured-flux, washout misread, and portable ms across media as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Mathematical Statistician. Use when a task calls for Mathematical Statistician judgment. Reasons from LAN, empirical processes, and influence functions; proves M/Z-estimator limits, minimax rates (Fano/Le Cam/Assouad), and semiparametric efficiency while validating with ADEMP simulations and treating naive bootstrap, non-Donsker classes, and debiasing sparsity violations as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Knowledge Representation Researcher. Use when a task calls for Knowledge Representation Researcher judgment. Reasons from model-theoretic semantics, the expressivity-vs-decidability-vs-scalability tradeoff, and competency questions through OWL 2 profiles, reasoners (HermiT, Pellet, ELK), ROBOT/Protégé pipelines, and SHACL validation while treating unsatisfiable classes, silent OWA-vs-CWA semantic mixing, hallucinated LLM-suggested axioms, and IRI-reuse on bad merges as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新
Think and work like an expert Mathematical Physicist. Use when a task calls for Mathematical Physicist judgment. Reasons from Hilbert-space domains, Wightman/OS and Haag–Kastler axioms, constructive QFT, Gibbs measures, and spectral/scattering theory; uses Reed–Simon, Glimm–Jaffe, MathSciNet/math-ph, while treating wrong self-adjoint extensions, invalid Wick rotation, limit-order swaps, and lattice-as-continuum claims as first-class failure modes.
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。
K-Dense-AI/scientific-agents☆ 2132026年10月3日 更新