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Found 1,022 Skills
Author, scaffold, and run coding-agent-driven tests: Markdown case files executed by a coding agent against a live environment (browser, API, DB, logs, cloud, telemetry) with an auditable PASS/FAIL/BLOCKED report. Use when a deterministic test would be premature, brittle, too expensive, or too narrow.
Design, create, update, validate, and audit Codex/CCFA skills, trigger wording, resources, references, scripts, path privacy, family governance, and CCFA documentation SVG diagrams. Use for skill maintenance, new skill creation, routing conflict cleanup, Markdown/SVG docs maintenance, and release validation. Do not perform research writing or review work.
Conduct deep research using NotebookLM integration — upload documents, query with citation-backed answers, synthesize findings, and produce infographic-style presentations. Output in Markdown, HTML/reveal.js slides, or Mermaid diagrams with visual hierarchy design specifications.
Create professional presentations using the Pyramid Principle methodology. Supports PPTX generation, Marp/Reveal.js Markdown slides, chart creation, speaker notes, and self-evaluation rubrics. Minimal intake form to rapid output workflow.
Grades a specified set of test methods individually and produces a concise table mapping each test (fully-qualified name) to a letter grade (A–F), a score band, and a one-line note — designed to be posted as a PR comment. Use when the caller wants per-test feedback on a curated list of methods (for example, the new or modified tests in a pull request), not a suite-wide audit. Polyglot: .NET, Python, TS/JS, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, C++. Input is a list of test methods (or method bodies / file+line spans); output is a compact markdown table plus a short summary. DO NOT USE FOR: full suite audits (use test-quality-auditor agent or test-anti-patterns), writing new tests (use code-testing-generator agent or writing-mstest-tests), fixing failures, or measuring code coverage.
A skill for writing and revising Japanese business documents to make them easy to read and understand. It can be used for creating and proofreading business documents such as meeting minutes (including transcribing to minutes), research/analysis reports, internal guides/manuals, research notes, discussion papers, proposals, reports, emails, and slide outlines, as well as following instructions like 'write from the conclusion', 'clarify the argument', 'keep headings concise', and 'explain technical terms in an easy-to-understand way'. It also supports removing AI-like tones (direct, indirect, or colloquial feedback such as 'AI-like', 'unnatural', 'make it more natural Japanese', 'mechanical', 'make it sound human', 'monotonous', or phrasing like 'it would be possible to...', as well as cases where the document was said to be written by AI or suspected of being so), improving hard-to-read or unclear sentences (such as incorrect word order, long sentences, unclear meaning, incorrect comma placement, etc.), writing new note articles, blog posts, and essays (including requests to write from scratch on any topic), rewriting and polishing existing sentences, diagnosing and scoring AI-like tones (requests without rewriting, such as 'Did AI write this?', 'Score the AI-like tone', 'Judge how AI-like this is'), and requests to learn and profile one's own writing style (including requests to write in one's own style by reading past sentences). It also addresses readability principles such as removing forbidden words, avoiding monotonous rhythm, homogeneous paragraph structure, literal translation of English syntax, as well as word order, commas, one meaning per sentence, and the distance between subject and predicate. The structuring of technical documents or formatting of Markdown itself (such as one sentence per line, quote blocks, footnote notation, etc.) is not covered—this falls under another skill, and this skill specializes in the naturalness, readability, and comprehensibility of text.
Creates task-oriented technical documentation with progressive disclosure. Use when writing READMEs, API docs, architecture docs, or markdown documentation. Also use this skill at the END of any completed reverse engineering, penetration testing, CTF, or security analysis task to generate a formal report in the user's project directory. Trigger keywords: 写报告, 写文档, 出报告, writeup, 技术文档, report, documentation.
Use this skill whenever LMX is used, produced, reviewed, migrated, or modified. This includes composing campaigns, loops, lifecycle emails, or email-message bodies for the Loops editor or Content API. LMX (Loops Markup Language) is the format used for Loops email content. Trigger on phrases like "create a campaign", "generate an email", "write a welcome email", "draft a lifecycle email", "build an email template", "create an onboarding email", "copy this into LMX", "migrate this email", "convert this email to LMX", "design a new Loops email", "use imagegen for a Loops email", "use gpt-image for an LMX reference", "visual reference for a Loops email", "LMX", "Loops email", or any request to produce, copy, migrate, convert, review, or modify email body content intended for Loops. For net-new emails or major visual redesigns, follow this skill's Net-New Email Design Flow before generating or sourcing new visual assets. Source copy, existing HTML, MJML, Markdown, screenshots, and migration instructions do not bypass this skill's rules unless the user explicitly overrides a specific rule. Do not trigger for questions about the Loops HTTP API, SDK integration, or CLI unless email body content is also involved.
Executes real end-to-end verification against a running application after specification implementation. Detects the application type, starts the local runtime (Docker, Node, Spring Boot, etc.), runs real tests (curl for REST APIs, Playwright for web SPAs, computer-use for desktop apps), verifies acceptance criteria from the functional specification, generates a markdown report, and tears down the environment. Use when: user asks to verify a completed spec with real tests, run e2e checks after implementation, validate acceptance criteria in a live environment, or test the feature for real after task completion.
Fact lookup: Apple Human Interface Guidelines corpus (greppable markdown). Query on demand for accessibility and ergonomic minimums (hit-target sizes, Dynamic Type), platform terminology, system component capabilities, and App-Review-relevant conventions. Not design direction.
Bun runtime API reference for TypeScript scripts. Covers Bun.file(), Bun.write(), Bun.$() shell, Bun.spawn(), Bun.Glob, Bun.env, bun:sqlite, Bun.sql() for PostgreSQL/MySQL via DATABASE_URL, Bun.s3 for S3-compatible storage, Bun.redis for Redis/Valkey, Bun.Archive for tarballs, Bun.Image image processing, Bun.WebView headless browser automation, Bun.cron in-process scheduler, JSONC/JSON5/JSONL/markdown (named imports), Bun.hash, Bun.password, compression, and scripting utilities. Use when writing scripts, automating tasks, querying databases, working with S3 storage, Redis caching, processing images, automating a headless browser, parsing markdown/JSON variants, or doing file processing in a Bun project. Signals: bun.lock, bunfig.toml, DATABASE_URL, REDIS_URL, AWS_ACCESS_KEY_ID, Bun.$ usage Not for bun CLI commands (bun-cli skill), non-Bun runtimes, or ORM CLI tooling
Scrape a single known URL into clean markdown / HTML / links / structured JSON with fastCRW. Use when you already have the URL and want the page content — "scrape", "grab", "fetch", "pull", "read this page", "get the content of". Handles JavaScript-rendered SPAs automatically. Step 2 of the crw workflow ladder.