「md」の検索結果

Use when a user wants to convert any markdown file in their Claude project into a single-file, lightly-interactive HTML — long-form documents (specs, plans, RFCs, reports, explainers), code reviews with diffs and severity-tagged annotations, or slide decks. Triggers on "convert this markdown to HTML", "make this an HTML file", "turn this into an interactive document", "render this report as HTML", "PR writeup as HTML", "slides from this markdown". Forks context to route to one of three converter sub-skills (md-document, md-review, md-slides) based on a deterministic doctype classifier, after the user has run the design-system onboarding once. Refuses if input is under 100 lines (per Shihipar — markdown still wins below the threshold) or design-system isn't onboarded. Distinct from Anthropic's official Playground plugin (which is interactive prompt-tuning controls with sliders/knobs/prompt-copy-back) and from marketing/landing/ (which is a landing-page generator).

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。

Converts a markdown deck (slides separated by `---` HR boundaries or by `# ` H1 headings, with optional `<!-- notes: ... -->` presenter notes blocks) into a single-file HTML presentation with arrow-key / space / PgDn / PgUp / Home / End / P / Esc keyboard navigation, presenter mode (split view with current slide + speaker notes + clock + next-slide preview), URL-hash deep linking, and `@media print` page-per-slide for PDF export. Triggers when the markdown-html-orchestrator classifies an input as SLIDES, or when invoked directly via /cs:md-slides. Reuses md-document's markdown parser for slide-body rendering and reads design-system tokens via config_loader.py. Refuses if input has no clear slide boundaries, produces a 1-slide deck, or `--strict-notes` is on with < 50% notes coverage. Use after orchestrator routing.

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。

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Kiro skill instructions and steering state read selected project planning context. Recovery reads project planning files and their timestamps only, not agent transcript stores. This adapter registers no Stop hook, never requests continuation, and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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。

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; agent instructions read selected project planning context when invoked. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. This adapter registers no lifecycle or Stop hook, never requests continuation, and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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。

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; Gemini lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. The session-end hook reports status only; it does not request continuation or run commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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。

Planificación persistente basada en archivos para tareas multipaso de agentes de IA. Mantiene task_plan.md, findings.md y progress.md en disco; los hooks del ciclo de vida inyectan contexto seleccionado de planificación del proyecto. La recuperación automática solo lee los archivos de planificación del proyecto. session-catchup.py --metadata, solicitado de forma explícita, puede inspeccionar metadatos locales de sesiones del mismo proyecto; --replay puede emitir extractos limitados y enmarcados con nonce. El modo con gate opcional solo puede solicitar que el host continúe si este lo admite y nunca ejecuta comandos declarados en Markdown. El skill no tiene ninguna ruta de carga por red. Úsalo para investigación o trabajo que requiera 5 o más llamadas a herramientas.

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。

用於多步驟 AI 代理工作的持久化檔案規劃。將 task_plan.md、findings.md 與 progress.md 保存在磁碟上，生命週期鉤子會注入選定的專案規劃內容。自動恢復只讀取專案規劃檔案；只有明確執行 session-catchup.py --metadata 才會檢查本機同一專案的代理工作階段中繼資料，--replay 則會輸出有界且以 nonce 框定的摘錄。選用的閘門模式只會在主機支援時要求繼續，而且絕不執行 Markdown 中宣告的命令。此技能沒有網路上傳路徑。適用於研究或需要超過 5 次工具呼叫的工作。觸發詞：任務規劃、專案計畫、制定計畫、分解任務、多步驟規劃、進度追蹤、檔案規劃、幫我規劃、拆解專案

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。

Persistente dateibasierte Planung für mehrstufige Arbeit mit KI-Agenten. Hält task_plan.md, findings.md und progress.md auf dem Datenträger; Lebenszyklus-Hooks speisen ausgewählten Planungskontext des Projekts ein. Die automatische Wiederherstellung liest nur die Planungsdateien des Projekts. Nur ein ausdrücklicher Aufruf von session-catchup.py --metadata darf lokale Sitzungsmetadaten desselben Projekts prüfen; --replay darf begrenzte, nonce-gerahmte Auszüge ausgeben. Der optionale Gate-Modus kann nur bei Unterstützung durch den Host eine Fortsetzung anfordern und führt niemals in Markdown angegebene Befehle aus. Der Skill hat keinen Netzwerk-Uploadpfad. Verwenden für Forschung oder Arbeit mit mehr als 5 Tool-Aufrufen.

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。

用于多步骤 AI 代理工作的持久化文件规划系统。将 task_plan.md、findings.md 和 progress.md 保存在磁盘上，生命周期钩子会注入选定的项目规划上下文。自动恢复只读取项目规划文件。只有显式运行 session-catchup.py --metadata 才会检查本机同项目的会话元数据；--replay 可输出有长度限制且由 nonce 框定的同项目摘录。可选门禁仅在宿主支持时请求继续，绝不执行 Markdown 中声明的命令。本技能没有网络上传路径。适用于研究或需要 5 次以上工具调用的工作。触发词：任务规划、项目计划、制定计划、分解任务、多步骤规划、进度跟踪、文件规划、帮我规划、拆解项目

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。

تخطيط مستمر قائم على الملفات لعمل وكلاء الذكاء الاصطناعي متعدد الخطوات. يحتفظ بملفات task_plan.md و findings.md و progress.md على القرص، وتحقن خطافات دورة الحياة سياق التخطيط المحدد للمشروع. تقرأ الاستعادة التلقائية ملفات تخطيط المشروع فقط. يمكن للأمر الصريح session-catchup.py --metadata فحص بيانات وصفية لجلسات الوكيل المحلية التابعة للمشروع نفسه، بينما قد يصدر --replay مقتطفات محدودة مؤطرة بقيمة nonce. يمكن للوضع المحكوم الاختياري طلب المتابعة فقط عندما يدعمه المضيف، ولا ينفذ أبدًا أوامر معلنة في Markdown. لا تتضمن المهارة مسارًا لرفع البيانات عبر الشبكة. تُستخدم للبحث أو العمل الذي يحتاج إلى 5 استدعاءات أدوات أو أكثر.

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。

Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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。

Knowledge and governance closeout: reconcile project docs, rule files (CLAUDE.md/AGENTS.md), authorized agent memory, and workspace residue with what the code and runtime actually do, so the next session or the next person starts from one current answer. Trigger when the user names "neat-freak", "洁癖", or "/neat" — and also on clear knowledge-closeout intent without the name: syncing or tidying project docs/rules/memory after development ("把文档和记忆整理一下", "收尾时把文档同步掉", "docs 和代码对不上了"), stale or conflicting CLAUDE.md/memory, a clean handoff to a teammate or a fresh session, or auditing whether workspace rules are actually followed. Do not trigger for pure coding/refactoring/debugging tasks, tidying data or prose (JSON, 周报, changelog announcements), or a bare "整理" with no project-knowledge context.

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Intakes external content, classifies chunks against LifeOS taxonomy, commits with provenance. Sources: .md/.txt, stdin, LifeOS dirs, CLAUDE.md/Cursor/OpenAI Custom Instructions, Obsidian/Notion/Apple Notes exports. MigrateScan classifies → routing table. MigrateApprove with --approve-all/--approve-target/--review/--dry-run. Confidence ≥70% auto, 40-70% confirm, <40% walk-through. USE WHEN /migrate, migrate content, import from other LifeOS, bring in old notes, import Cursor rules, import CLAUDE.md, bulk import, Obsidian/Notion/Apple Notes import. NOT FOR single-file edits, conversational interviews, identity edits.

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。

Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.

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。

Submit compact HMDB search requests for metabolites, proteins, diseases, and pathways. Use when a user wants concise HMDB summaries

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Evaluate a repo agent harness (AGENTS.md, rules, skills, skill refs) for broken paths/commands, redundant instructions, and usefulness using a stack-agnostic dual-judge protocol with planted traps. HIGH PRIORITY questionnaires at top: Q1 optional docs, Q2 B/C budget before Track A (certainty/tokens). A always runs after Q2; B/C opt-in. ADRs/RFCs excluded from T2. Mixed apply uses 11-mixed-apply.md (KEEP/CUT). Use when the user says harness eval, harness-eval, harness debug, audit AGENTS.md, audit skills/rules, instruction audit, redundancy of agent instructions, usefulness of skills, Ship/Review/Hold/Slim/Keep-core for harness, or wants Track A/B/C harness evaluation. Do NOT use for harness setup or init, feature spec-driven work (tlc-spec-driven), or applying Ship/Slim trims unless the user explicitly asks after the report.

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Design, implement, optimize, and review SIMD code in .NET. USE FOR: vectorizing scalar loops with TensorPrimitives, Vector64/128/256/512, or platform hardware intrinsics; reviewing existing SIMD code, including the generic Vector type, for contract equivalence, tail handling, memory safety, portability, fallbacks, and measured performance. DO NOT USE FOR: performance work unrelated to SIMD or vectorization.

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Generate an enterprise-style changelog for a PipesHub GitHub release. Takes a release URL or tag (e.g. https://github.com/pipeshub-ai/pipeshub-ai/releases/tag/v0.5.0 or v0.5.0), writes the detailed per-release changelog to changelog/<version>.md, and registers it in the repo-root CHANGELOG.md (condensed entry + link) and the changelog/README.md index.

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Perform cross-artifact consistency analysis across spec.md, plan.md, and tasks.md. Use after task generation to identify gaps, duplications, and inconsistencies before implementation.

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Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.

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Maintain this CCB project's GitHub-facing release and npm publication surface. Use when preparing, publishing, auditing, or fixing CCB releases; updating README.md, README/zh.md, localized README files, CHANGELOG.md, VERSION, package.json, GitHub release notes/assets, repository description/topics, npm registry state, or GitHub Actions release/test status.

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Golang skills orchestrator — always active on any Golang coding, review, debug, or setup task. Reads the task context and loads the most relevant skills from samber/cc-skills-golang, often multiple at once: writing a gRPC service loads golang-grpc + golang-testing + golang-error-handling; debugging a panic loads golang-troubleshooting + golang-safety; auditing security loads golang-security + golang-lint + golang-safety. Also: disambiguates competing clusters when two skills seem to overlap (performance vs benchmark vs troubleshooting, samber/lo vs mo vs ro, DI cluster, safety vs security), and configures the project's agent-config file (CLAUDE.md, AGENTS.md, GEMINI.md, Cursor rules, or Copilot instructions) to force-trigger skills in a project (/golang-how-to configure).

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。

Generates AGENTS.md files for repository folders — coding agent context files with build commands, testing instructions, code style, project structure, and boundaries. Only generates where AGENTS.md is missing.

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。

SUPERSEDED by /claudex-loop (formerly /crucible; its docs-aware mode covers this variant) — prefer that skill unless you explicitly want this one. Two-act plan hardening with living documentation. ACT 1 (you ↔ Claude) — Claude interviews you relentlessly about a plan, one question at a time, challenging it against your project's existing domain model and glossary (CONTEXT.md), sharpening fuzzy terms, stress-testing with concrete scenarios, cross-referencing code, and updating CONTEXT.md + ADRs inline as decisions crystallise. ACT 2 (Claude ↔ Codex) — Claude writes the locked plan to PLAN.md and OpenAI Codex adversarially reviews it in a read-only sandbox (VERDICT:APPROVED/REVISE), Claude revises and re-submits to the SAME Codex session until APPROVED or a MAX_ROUNDS cap, then you sign off before any code. Use when the user says "/grill-with-docs-codex", "grill me against the docs then have codex review", "stress-test this against our domain model then get a second model on it", or is about to build something high-stakes in a project with established terminology/ADRs and wants alignment, documentation, AND a cross-model sanity check. Builds on Matt Pocock's grill-with-docs (MIT). NOT for reviewing already-written code (use /codex:review) and NOT for trivial changes.

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。