Productivity Claude Skills
3 457 productivity skills from 510 authors. They keep notes, tasks, calendars and plans in order. Half of them fit into 1 851 tokens or less — that is what one costs your context window when the agent loads it. 479 ship runnable scripts rather than instructions alone. 51 of them cannot work without an MCP server, most often rube. We also found 336 copies of these same skills sitting in other people's repositories — counted once here, not 336 times.
3 457 unique 510 authors 2 021 updated this month 293 from vendors
Expert startup business analysis for market sizing, financial modeling, competitive analysis, and strategic planning. Use PROACTIVELY when the user asks about TAM/SAM/SOM, financial projections, unit economics, competitive landscape, team planning, startup metrics, or early-stage business strategy.
定时巡检 agent 任务执行状态，识别卡住、abort、无产出等异常并触发催促或告警。
团队协调与智能任务分配。作为高管，将用户任务拆解并分配给最合适的员工 agent 执行，协调多 agent 并行协作，汇总审核产出。
This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical decisions. Provides systematic multi-source research and synthesized recommendations.
蒸馏Andy Grove思维模式的实用框架——高产出管理、OKR、战略转折点、只有偏执狂才能生存
Automate Todoist task management, projects, sections, filtering, and bulk operations via Rube MCP (Composio). Always search tools first for current schemas.
口播视频转录和口误识别。生成审查稿和删除任务清单。触发词：剪口播、处理视频、识别口误
微信朋友圈AI雷达 — 自动化采集276+条朋友圈内容，通过AI视觉提取、分类分析、商机发现，生成结构化简报。支持每日定时任务，一键生成热点报告。
Generate Xiaohongshu (小红书/RED) content optimized for the platform''s social media content for RED, (3) generating content with xiaohongshu SEO optimization, (4) planning xiaohongshu content calendars. Supports diary-style, tutorial, review, and list formats with proper AI content labeling.'
OpenTelemetry Semantic Conventions expert. Use when selecting, applying, or reviewing telemetry attributes. Triggers on tasks involving attribute selection, semantic convention compliance, attribute migration, or custom attribute decisions. Covers the attribute registry, naming patterns, attribute placement, and versioning. For span names, span kinds, and span status codes, see the otel-instrumentation skill.
把执行性编码/调查任务整包交给 DeepSeek 后台执行，省主会话额度。后台运行，完成后自动通知。支持并行多任务，支持续接（resume）上次会话继续派发后续任务。
向 Codex (GPT-5.6) 咨询复杂问题 / 要第二意见 / 派发需要强推理的任务。后台运行，完成后自动通知。支持并行多任务，支持续接（resume）上次会话继续派发后续任务。
把执行性编码/调查任务整包交给 gemini 后台执行，省主会话额度。后台运行，完成后自动通知。支持并行多任务，支持续接（resume）上次会话继续派发后续任务。
把关键决策/验收类任务交给 Claude Opus 执行。后台运行，完成后自动通知。支持并行多任务，支持续接（resume）上次会话继续派发后续任务。
> Receive and verify Jira Cloud webhooks. Use when setting up Jira webhook handlers, debugging signature verification, or handling issue and comment comment_created, or comment_updated.
> Receive and verify Nylas webhooks. Use when setting up Nylas webhook handlers, debugging x-nylas-signature verification, completing the challenge handshake, or handling email and calendar events like message.created, message.opened, event.created, event.updated, or grant.expired.
CRE Closing management suite — 2 specialist skills for closing checklist coordination and funds flow preparation for multifamily acquisitions.
CRE Asset Management analysis suite — 9 specialist skills for post-acquisition multifamily operations including annual budgeting, monthly variance analysis, rent collection, renewal decisions, lease-up tracking, capex execution, NOI improvement, hold/sell/refi scenario analysis, and quarterly asset review memos.
>- Manage Harness Internal Developer Portal (IDP) resources via MCP. Create service catalog templates, configure self-service environment provisioning workflows, generate service documentation, create Architecture Decision Records (ADRs), and design developer onboarding workflows. Use when asked to set up a service catalog, create self-service workflows, generate service docs, write ADRs, or onboard new developers. Do NOT use for service scorecards (use scorecard-review instead). Trigger architecture decision, service documentation, catalog template, developer experience, backstage.
> Summons a Council of 7 expert AI personas to debate any decision, idea, problem, or question from radically different perspectives — then synthesizes a structured verdict with confidence score, critical risks, and action steps. Use this skill whenever someone wants a decision analyzed, an idea stress-tested, a strategy evaluated, a career choice examined, a technical architecture reviewed, a business plan critiqued, a creative project assessed, or any situation where getting multiple expert viewpoints would lead to a better outcome. Trigger on phrases like "should I", "what do you think about", "help me decide", "review my", "is this a good idea", "council", "debate this", "stress-test", "get different perspectives on", "what are the pros and cons of". Also trigger when someone describes a plan, idea, or dilemma even without an explicit question — if it sounds like a decision worth examining from multiple angles, convene the Council.
Use when a durable technical decision was just made in conversation and should be recorded, or when user asks to write/record an ADR (開 ADR / 記個決策 / 這要不要 ADR). Runs a three-gate check FIRST and actively talks the user out of writing one when the decision doesn't qualify — then writes a lightweight (title + 1-3 sentences) ADR following the repo's own ADR conventions if any exist. Repo conventions always override this skill's defaults. NOT for requirement specs (spec / prd-create) or for rewriting history (superseded ADRs get a new ADR, never an edit).
Use when user wants to break a PRD into Azure DevOps work items via vertical-slice plan. Workflow: read PRD → quiz user to lock durable decisions → draft slices with HITL/AFK + blocked_by → call az CLI directly via Bash to create items + Predecessor relations. Idempotent re-runs via fingerprint markers embedded in description. Pure prompt-driven — Claude is the runtime, no Python helper, no install ceremony. Trigger phrases: prd-breakdown / 拆 PRD / 切 vertical slice / 推 slice 到 ADO.
Use when user wants to draft a PRD (Product Requirements Document) from raw input (meeting transcripts, hand-waved descriptions, scattered decisions). Workflow: load org's PRD Guideline + writing discipline → lock execution mode (human-run vs unattended-agent-run) → ingest raw input → quiz user numbered-list iterate to fill §1-§15 → draft v0.1 → handle stakeholder merge (review feedback, surface conflicts) → lock v1.0 + sanitize per ADO publication contract → publish to ADO Wiki. For an agent-run PRD, §13 carries the unattended-execution discipline (machine-checkable AC + traffic-light + 3-exits + stop-and-ask), aligned with goal-engineer's loop-run-protocol. NOT for packaging an ALREADY-FROZEN build spec (approved ADR / locked design / machine-checkable AC) into an unattended dispatch — that is goal-engineer's lean build dispatch. Pure prompt-driven — Claude is the runtime, no Python helper. Trigger phrases: 寫 PRD / PRD 撰寫 / prd-create / 初版 PRD / 起 PRD.
Use when the user wants a spec-driven development workflow for implementing a feature in the current codebase, from fuzzy idea or existing active spec through requirements, technical plan, tasks, implementation, verification, and closure report. Auto-detects project/spec state, writes persistent files under specs/, asks one grounded question at a time when requirements are ambiguous, and stops at stage gates. NOT for stakeholder PRDs (prd-create), ADO ticket breakdown (prd-breakdown), single architecture-decision records (adr), or already-frozen tasks that should simply be implemented.
Use when the user is unsure which kc_ai_skills workflow skill to use, or describes work involving PRD, SD/software design, FR, AC/acceptance criteria, ADR, tickets, implementation, debugging, release checks, or unattended agent execution. Triage the request with at most one clarifying question when needed, explain the route in plain language, then hand off to the right specialist skill. This is an entry router only: it does not write PRDs, specs, ADRs, tickets, or dispatches itself.
>- Parallel-research-then-converge design workflow between two agents. Use this skill when the user wants two agents to independently think through a design problem before aligning on a solution — "spec X with codex", "design X together", "both agents think through X", "brainstorm architecture together", "parallel research then joint proposal", "think through separately then align", "careful thought from both sides before coding", or any variation where the user wants collaborative design rather than just splitting implementation work. Also use this when you receive a message labeled sending simple messages or reviews (use /amq-cli), implementing completed designs, or creating document templates.
| 即使用户只是说"我的 Obsidian 堆了一堆没处理的东西",也应该触发。
Organize files into target directories based on classification results
Find available time slots in a calendar and schedule meetings while respecting constraints
Extract calendar events, blocks, and time slots from PDF calendar files using pdfplumber
Plan multi-city road trip routes using distance matrices and constraints
Techniques for parsing visual calendar PDFs to extract appointment blocks, free slots, and time boundaries.
Planning multi-city travel itineraries with budget constraints, route optimization, and cuisine diversity.
Querying travel planning datasets (cities, restaurants, accommodations, attractions, distances) for itinerary generation.
Workflow for creating and applying patches to Java projects - diff format, patch application, and Maven rebuilds for security fixes.
Organize files into subject folders using keyword-based classification of titles and abstracts, with fallback to full text extraction.
Use PyMuPDF (fitz) to extract visual calendar blocks from a PDF, including color detection and pixel-to-time conversion.
Extract text and identifying colored regions (e.g., rectangles) from a PDF using pdfplumber.
Use a distance matrix CSV to find travel time and distance between cities for self-driving trips.
Logic for calculating meeting slots based on constraints and availability.
Extracts vector graphics, colors, and text from PDF files using PyMuPDF to analyze calendars or visual schedules.
Uses regular expressions to parse dates, time ranges, and durations from natural language text like meeting requests.
Algorithmic planning of itineraries avoiding specific transport modes and allocating time based on budget constraints.
Comprehensive checklist to verify a completed seven-character regulated verse meets all requirements
Extract calendar event times by analyzing visual block positions relative to hour markers
Complete NML-based GLM calibration workflow with validation and verification
Comprehensive rules, tonal patterns, and verification checklist for composing a seven-character regulated verse (七言律诗).
Schedule meetings into calendar free slots considering time constraints, timezone conversion, and blue-block overrides.