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Mine Claude Code session data for analytics — token usage, tool rankings, skill invocations, session search, and prompt history. Use when asked about session stats, token costs, tool frequency, skill usage patterns, or finding past sessions by prompt text.

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Break an application or feature into thin vertical user-story slices with clear acceptance criteria and user-observable value. Use when planning a backlog, decomposing a feature, writing implementation-ready stories, or turning requirements into deliverable slices.

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Rebuilds session context after a clear by reading git history, plans, and beads state. Triggers on 'catch up'.

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Split user stories into smaller, independently deliverable slices using the SPIDR method (Spike, Path, Interface, Data, Rules). Use this skill whenever the user asks to split a story, break down work, slice a story, asks "can this be split", mentions "SPIDR", says "story splitting", or wants to decompose a large ticket into smaller pieces. Also trigger when a user presents a story that seems too large for a single sprint and asks for help sizing or scoping it.

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Use when the user asks to create, add, convert, publish, or deploy a blog post from a draft, notes, Markdown, outline, or topic. Turns a draft into a complete, SEO/GEO-optimized post wired into the site (template, blog index, sitemap, routing) with QA and deploy. Framework-agnostic — discover the project's own conventions first.

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Use after PROJECT_GUIDE.md exists, when the user asks if a project is worth their time, should they build vs buy, or invokes project-worth-my-time. Follow-up to explain-new-project—weighs project context (files, git history, chat) to recommend whether to invest in a repo, cherry-pick a feature, park the idea, pass, or use an existing polished product instead. Optionally enriched by a personal-memory MCP (e.g. Pieces) when one is available.

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Retrieve the current system date and time to anchor the agent in present reality. Use for questions involving today, current time, recent events, or information newer than the model's training data to prevent knowledge-cutoff errors and fictionalization of real facts.

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Triage a GitHub issue that already has the cc-issue-created label and is assumed to be ready to start. First inspect the comment history to decide whether human confirmation is needed (cc-need-human-check, highest priority); otherwise decide whether the issue should be closed as not needed, unanswered confirmation items remain (cc-answer-issue-questions), the description is stale relative to settled comment-history content and must be refreshed before execution (cc-update-issue), or it can move to execution (cc-exec-issue). Dependency checks are out of scope.

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Virtual QA Lead that turns requirements into review-ready, TestRail-importable test cases in one conversation. Use it whenever the user has requirements, a spec, a user story, or acceptance criteria (PDF, DOCX, XLSX, TXT, MD, or pasted text) and wants test cases, a test plan, a checklist, test coverage, a regression suite, or a TestRail/Qase/Zephyr export, even without saying "test cases" ("write tests for this spec", "what should we check here?"). Especially useful when they attach their team's existing test cases to match. When the spec describes an API (endpoints, status codes, schemas, auth, OpenAPI/Swagger), Casely also builds a runnable Postman collection, so use it for "API tests", "Postman collection", or "tests I can run in Newman/CI". Triggers on the same request in any language.

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Transforms data into compelling visual narratives by applying narrative structure, annotation techniques, scrollytelling patterns, and honest framing to data journalism, presentations, and infographics. Use when creating data-driven articles or reports, designing infographics with narrative, building scrollytelling experiences, annotating charts to guide interpretation, or when user mentions data storytelling, presentation design, annotated chart, narrative visualization.

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Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

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WeChat article creator with Fu Sheng's writing style - conversational, story-driven, opinionated. Use this skill whenever the user mentions writing a WeChat article, drafting public account content, crafting a viral headline, creating article covers, writing in Fu Sheng's style, or any request involving 公众号, 微信文章, 爆款标题, or 傅盛风格 — even if they don't explicitly say "skill".

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The HyperFrames composition contract — build one renderable project. Use for composition structure, the `data-*` timing attributes, `class="clip"`, tracks, sub-compositions, variables, framework-owned media playback, deterministic-render rules, and validation. Also covers Tailwind projects and the STORYBOARD.md / SCRIPT.md plan formats. Read before writing composition HTML.

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Build an interactive, drag-and-drop user story map so the user can re-slice work across release phases. Use when the user wants a story map, a phased roadmap, release slicing, a backbone/activities journey map, or to decide "which stories go in which phase" and move them around.

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Preview a signed-off design one release phase at a time — cut it down into a series of phase screens, each showing only what exists by that phase with the layout untouched, then put them on a scrubber you drag to watch the screen fill in release by release. Use when the user wants a Phase 1 / MVP version of an existing wireframe or mockup, phased or staged screens, a design sliced by release phase or story map, or wants to see what a screen looks like before later features land.

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Build one release phase against the specs — plan it on an interactive board (endpoints, components, resources, with what already exists read from the codebase), let the user adjust, then build node by node while the board shows live progress. Use when the user wants to build a phase, implement the phase-1 slice, execute the plan from a story map or spec, or watch a build happen visually.

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Use when editing Chinese web fiction, narrative prose, or story drafts that sound AI-generated, overly polished, formulaic, explanatory, or too symmetrical; use to detect AI-writing fingerprints and revise only wording while preserving plot, facts, characters, names, and intent.

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話の順序と頁の役割を先に決め、内容に合う部品とテーマ固有の図へ渡して、検査付きの編集可能資料へ組む。

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人前で話す登壇・講義スライドのストーリーの組み方。つかみ、中扉、段階的な開示、見出しの文体、締め方、尺の見積り。「登壇スライドを作って」「LTの資料」「講義資料の構成を考えて」と言われたら、書き始める前に読む。

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Create, critique, and repair high-quality presentation decks with a story-first, output-engine-aware workflow. Use when the user asks for PPT, PowerPoint, slides, deck, pitch deck, keynote, course deck, academic deck, consulting deck, HTML slides, web presentation, image-first slides, social carousel, speaker notes, deck outline, slide plan, template replication, deck review, deck polish, or conversion from documents, articles, Markdown, PDFs, URLs, or existing .pptx files. Also use when the user says Knowledge Cat PPT or asks for an industry-grade presentation skill.

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原稿→構成→スタイル→ページ制作の分離を継承。日本語の教材へ再設計し、図解と文字を編集可能にします。 単なる既存文章の校正には使わない。

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When the user wants to edit, review, or improve existing marketing copy — 'edit this copy,' 'proofread,' 'polish this,' 'tighten this up,' 'too wordy,' 'sharpen the messaging.' Use when copy exists and needs improving, not rewriting from scratch. For writing new copy, see copywriting.

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Analyzes git diffs or staged changes and generates narrative commit messages that explain WHY a change was made, not just what changed — following Conventional Commits format. Use when asked to "write a commit message", "generate a commit", "describe my changes", "what should I commit this as", "commit this", "summarize my diff", or "help me commit". Works with git diff output, staged files, or plain descriptions of changes.

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Use when designing or auditing long-term memory for persistent AI agents. Stores immutable source evidence before canonical facts, links beliefs to provenance, applies novelty-aware ADD/UPDATE/NOOP write gating, keeps uncertain merges explicit, separates retrieval from answer generation, supports deletion, and evaluates memory failures layer by layer.

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