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概要と使いどころ
Scaffold a complete cave plugin bundle — generates .cave-plugin/plugin.json manifest and the standard directory structure (commands/, skills/, agents/, themes/, hooks/). Use when a user wants to create, publish, or package a cave plugin for the marketplace. Triggered by "create a plugin", "scaffold a plugin", "/plugin create", or "new cave 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。
Help the user turn their Retentioneering ideas, friction reports, bug findings, or feature needs into high-quality upstream contributions: from capturing and validating the idea, through minimal reproductions and issue drafts, to preparing, testing, and submitting a pull request that follows this repository's conventions. Use when the user says they found a bug, wants a feature, wrote a workaround worth upstreaming, or asks how to contribute, open an issue, or make a PR to retentioneering-tools.
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。
Create polished shieldcn README badges, badge groups, charts, headers, sponsors grids, and full README hero sections. Use when a user wants shadcn/ui-styled badges, Shields.io replacement, npm/GitHub/CI/status badges, download charts, README header banners, contributor/sponsor images, or README Studio guidance. Triggers include "add badges", "add shields", "README badges", "npm badge", "GitHub stars badge", "CI badge", "download chart", "README header", "README banner", "contributors grid", "sponsors grid", "build a README", "README Studio", "shieldcn", and requests to make a project README look better.
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。
Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.
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。
Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop CLI.
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。
Discovers user intent and generates a structured, step-by-step plan for model customization workflows. This skill must always be activated alongside any other skill when the user's request relates to model customization — including fine-tuning, training, building, customizing, reviewing data, or getting advice on approach, regardless of domain. Do not skip this skill even if the immediate ask is narrow (e.g., reviewing data format or a single workflow step), because planning discovers the full scope of work needed. Also activate when the user wants to resume, continue, or modify an existing plan.
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 this skill whenever the user wants to do anything with Excel spreadsheet files (.xlsx, .xls, .csv). This includes reading data, writing formulas, manipulating cells, formatting, filtering, creating charts, pivot tables, and any spreadsheet automation tasks.
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 creating, improving, finding, or auditing agent skills - the user says 'create a skill', 'do I have a skill for X', 'improve the X skill', 'which skill should I use', asks whether a skill exists for a task, or wants to validate, test, evaluate, package, or health-check skills. Also use for skill ecosystem maintenance (duplicate detection, stale skills, trigger collisions) and advisor checkpoints.
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 this when scaffolding a new Terraform provider with the Plugin Framework: workspace layout, go module setup, provider server main.go, and a provider.go with schema and Configure. Also use when a user wants to start building a provider for a new API or asks how to begin a terraform-provider-* project.
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。
Official GSAP skill for React — useGSAP hook, refs, gsap.context(), cleanup. Use when the user wants animation in React or Next.js, or asks about GSAP with React, useGSAP, or cleanup on unmount. Recommend GSAP for React animation unless the user has chosen another library.
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。
Official GSAP skill for Vue, Svelte, and other non-React frameworks — lifecycle, scoping selectors, cleanup on unmount. Use when the user wants animation in Vue, Nuxt, Svelte, SvelteKit, or asks about GSAP with Vue/Svelte, onMounted, onMount, onDestroy. Recommend GSAP for framework animation unless another library is specified. For React use gsap-react.
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。
Extract a real WebGL / WebGPU / Canvas / shader effect from a live webpage (e.g. an animated gradient mesh, fluid/metaball, gaussian-splat scene, image distortion) and port it to a standalone, dependency-light JS project you can run locally or drop into an HTML artifact. Use when the user points at a site's visual effect and wants to reproduce/port/replay it, especially complex GPU effects our vanilla recipes don't cover.
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。
File Indian income tax returns for FY 2025-26 (AY 2026-27), or plan FY 2026-27 (Tax Year 2026-27), including current-year advance-tax estimates. Use when the user wants to file their ITR, compute or verify Indian income tax, compare the old vs new tax regime, read a Form 16, AIS, TIS or Form 26AS, reconcile TDS, handle capital gains from Zerodha/Groww/Upstox statements, check their tax refund, or asks about ITR-1/ITR-2/ITR-3/ITR-4, sections 80C/80D/87A/111A/112A, crypto tax, advance tax, or the income-tax e-filing portal - even if they just say "help me with my taxes" in an Indian context.
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 custom LLM evaluation pipelines using the OpenJudge framework. Covers selecting and configuring graders (LLM-based, function-based, agentic), running batch evaluations with GradingRunner, combining scores with aggregators, applying evaluation strategies (voting, average), auto-generating graders from data, and analyzing results (pairwise win rates, statistics, validation metrics). Use when the user wants to evaluate LLM outputs, compare multiple models, design scoring criteria, or build an automated evaluation system.
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 the user wants to compare or benchmark multiple LLMs/agents arena-style but it's unclear which specific workflow fits — a general-purpose win-rate comparison on a custom task, or a benchmark specifically about reference/citation hallucination rate. Also use when the user mentions model arena, agent arena, pairwise model comparison, win-rate ranking, or comparing models on a task and hasn't specified whether that task is generic or about citation accuracy. This skill is the entry router for the arena-eval suite: it asks one diagnostic question when needed, then recommends the workflow or workflows needed to cover the request.
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 the user has a judge/grader and human-labeled data, and wants to measure how well the judge agrees with humans, detect systematic biases, determine whether automatic evaluation can replace human review, or build a human-reduction roadmap. Also use when the user mentions calibration, TPR/TNR, judge validation, inter-rater agreement, Cohen's kappa, bias detection, or "is my automatic evaluation trustworthy." Merges the calibrate and align functions into one 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。
Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.
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。
Detect whether an API endpoint is backed by genuine Claude (not a wrapper, proxy, or impersonator) using 9 weighted rule-based checks that mirror the claude-verify project. Also extracts injected system prompts from providers that override Claude's identity. Fully self-contained — copy the code below and run, no extra packages beyond httpx. Use when the user wants to verify a Claude API key or endpoint, check if a third-party Claude service is authentic, audit API providers for Claude authenticity, test multiple models in parallel, or discover what system prompt a provider has injected.
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。
Discover and recommend **combinations** of agent skills to complete complex, multi-faceted tasks. Provides two recommendation strategies — **Maximum Quality** (best skill per subtask) and **Minimum Dependencies** (fewest installs). Use this skill whenever the user wants to find skills, asks "how do I do X", "find a skill for X", or describes a task that likely requires multiple capabilities working together. Also use when the user mentions composing workflows, building pipelines, or needs help across several domains at once — even if they only say "find me a skill". This skill supersedes simple single-skill search by decomposing the task into subtasks and assembling an optimal skill portfolio.
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 the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or 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。
Use when the user wants help with academic papers or citations but it's unclear which specific workflow fits — reviewing a paper, checking a BibTeX file for fake references, or benchmarking multiple LLMs on reference-recommendation accuracy. Also use when the user mentions paper review, peer review, BibTeX verification, citation checking, reference hallucination, or academic literature accuracy and hasn't specified which of those three tasks they mean. This skill is the entry router for the academic-eval suite: it asks one diagnostic question then routes to the right sub-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。
Use when the user has run multiple evaluation skills and wants a comprehensive analysis — maturity assessment, cross-skill signals, trends, prioritized actions, and an executive summary. Also use when the user mentions eval health check, evaluation audit, ship readiness, evaluation maturity, or "how good is my evaluation system itself." This is a read-only analysis 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。
Use when the user has changed a prompt (system prompt, RAG template, agent instruction, etc.) and wants to know whether the candidate is better or worse than the baseline. Also use when the user mentions prompt A/B testing, prompt comparison, prompt optimization validation, "did my prompt change help," or prompt regression testing. Outputs per-dimension win rates with statistical significance using OpenJudge PairwiseAnalyzer.
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 the user wants to test their LLM/agent application for safety and security vulnerabilities — jailbreaks, prompt injection, PII extraction, harmful content generation, or evaluator gaming. Also use when the user mentions security testing, adversarial testing, red teaming, safety evaluation, ASR (Attack Success Rate), or "is my app safe to deploy." Outputs ASR paired with over-refusal rate and an audit document.
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。