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 2 026 updated this month 293 from vendors
Produce the 12-month operational Yearly Planner — the calendar companion to the Growth Plan in Part 8. Translates strategy into month-by-month execution.
> Recommended repo-engineering guide when adding alerting to a PostHog product or extending the shared alerts platform. Routes lifecycle state machines, AlertPolicy, destinations, HogFunction dispatch, email, fixed-cadence and calendar scheduling, insight evaluation, the AlertWizard, and shared alert editor components. Use for product alert implementations, shared destination types, lifecycle or scheduling options, advanced alert settings, and platform alert infrastructure. Not for configuring alerts in an existing product.
Add a new warehouse-backed source to the PostHog Desktop Self-driving Inbox (the feature that ships GitHub, Linear, Zendesk, pganalyze, Jira). A source syncs one warehouse table (issues/tickets/conversations) and a cloud "signals scout" watches it and emits findings. Use when asked to "add a new inbox/self-driving source", "wire up <Jira/GitLab/Sentry/Intercom/Freshdesk/Front/Gorgias/etc> as a signal source", or to extend the source-toggle grid. Covers all three surfaces (posthog/posthog scout emitter + posthog/code UI wiring + the context-mill self-driving wizard skill that offers the source in `npx @posthog/wizard self-driving`), the deploy ordering between them, and created_via attribution.
> Use when adding or editing a GitHub Actions workflow, composite action, or reusable workflow under `.github/` — new CI jobs, triggers, matrices, checkout/clone tuning, action pinning, GitHub App token auth, concurrency groups, `timeout-minutes`, `paths` filters, caching, or runner choice. Not for debugging red CI (use debugging-ci-failures) or wiring a new secret end to end (use managing-github-actions-secrets).
> Build reusable dimension / lookup tables for a star schema — country/region, timezone, currency, date, plan/product, and other descriptive attributes — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to model dimension tables, lookup tables, a star schema, conformed dimensions, or wants to enrich events/revenue/usage with country, region, timezone, plan, or currency attributes without repeating JOINs. Covers sourcing the dimension data (upload, warehouse source, or derive from events), shaping it into an aliased one-row-per-entity view (optionally materialized on a slow schedule since dimensions change rarely), and attaching it to facts via a saved or person join so its hand-rolled rate table. Read modeling-warehouse-foundations first; dimensions here are reused by the revenue, conversion, activation, and product-usage modeling skills.
Build, edit, test, enable, and monitor PostHog workflows over MCP. Author the action/edge graph so it runs and opens cleanly in the visual editor, then change drafts surgically with patch operations. Use when asked to build, set up, automate, change, fix, or debug a workflow, campaign, broadcast, drip sequence, or event-triggered automation in the workflows product.
Expert knowledge for Azure DDos Protection development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when enabling DDoS IP/Network Protection, tuning policies, analyzing logs/metrics, or integrating NVAs and Azure Policy, and other Azure DDos Protection related development tasks. Not for Azure Firewall (use azure-firewall), Azure Firewall Manager (use azure-firewall-manager), Azure Web Application Firewall (use azure-web-application-firewall), Azure Virtual Network (use azure-virtual-network).
Expert knowledge for Azure Dedicated HSM development including troubleshooting, decision making, architecture & design patterns, and security. Use when deploying Dedicated HSMs, configuring VNet/ExpressRoute, planning HA/failover, or migrating to Managed HSM, and other Azure Dedicated HSM related development tasks. Not for Azure Cloud Hsm (use azure-cloud-hsm), Azure Payment Hsm (use azure-payment-hsm), Azure Key Vault (use azure-key-vault), Azure Confidential Computing (use azure-confidential-computing).
Expert knowledge for Azure DNS development including troubleshooting, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when automating DNS zones/records, using Private DNS/Resolvers, enabling DNSSEC, migrating legacy zones, or fixing name resolution, and other Azure DNS related development tasks. Not for Azure Traffic Manager (use azure-traffic-manager), Azure Front Door (use azure-front-door), Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager).
Expert knowledge for Azure IoT development including decision making, architecture & design patterns, and configuration. Use when managing Azure Device Registry X.509 PKI, ADR policies, IoT Hub cert revocation, or device schema namespaces, and other Azure IoT related development tasks. Not for Azure IoT Central (use azure-iot-central), Azure IoT Edge (use azure-iot-edge), Azure IoT Hub (use azure-iot-hub), Azure Defender For Iot (use azure-defender-for-iot).
Expert knowledge for Azure Lab Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring lab plans, VM templates/schedules, VNet-integrated labs, GPU/nested virtualization, or Canvas/Teams integration, and other Azure Lab Services related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).
Expert knowledge for Azure Site Recovery development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning ASR for VMware/Hyper-V, Azure VMs, physical servers, ExpressRoute, or multi-tier app DR, and other Azure Site Recovery related development tasks. Not for Azure Backup (use azure-backup), Azure Migrate (use azure-migrate), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Network (use azure-virtual-network).
Expert knowledge for SQL Server on Azure Virtual Machines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when planning SQL VM vs Managed Instance, Always On/FCI HADR, DTU/capacity, AHB licensing, or Blob backups, and other SQL Server on Azure Virtual Machines related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), Azure Virtual Machines (use azure-virtual-machines), SAP HANA on Azure Large Instances (use azure-sap).
Expert knowledge for Microsoft Foundry Tools (aka Azure AI services, Azure Cognitive Services) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Content Moderator, Content Safety, Content Understanding analyzers, REST/.NET APIs, or document extraction workloads, and other Microsoft Foundry Tools related development tasks. Not for Microsoft Foundry (use microsoft-foundry), Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local).
Maintains a repo-local task forest or task DAG for the current workspace. Use when the user asks to initialize, update, close a session, summarize evolving project tasks, decide whether a new request is a global task or subtask, track task progress/history/deviations/todos, export a task graph HTML, or provide task data for gap-router/local-agent-control-room. Do not use for executing the tasks themselves.
Applies language-agnostic and backend technical decision criteria, anti-pattern detection, debugging, and quality gates. Use when reviewing general/backend implementation choices, code smells, failures, or implementation completeness.
Applies React/TypeScript-specific technical decision criteria, anti-pattern detection, debugging, and frontend quality gates. Use when reviewing components, hooks, browser behavior, or frontend implementation completeness.
Implementation strategy selection framework. Use when planning implementation strategy, selecting development approach, or defining verification criteria.
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
Separates the outcome a change must produce from the requirements proposed to reach it, records what the user excluded, and bands cost from structure. Use when a requirement enters a workflow, before design begins.
Generate PRD and Design Docs from existing codebase through discovery, generation, verification, and review workflow
Generate PRD and Design Docs from existing codebase through discovery, generation, verification, and review workflow
Generate multiple diverse solutions in parallel and select the best. Use for architecture decisions, code generation with multiple valid approaches, or creative tasks where exploring alternatives improves quality.
Break down feature requests into detailed, implementable plans with clear tasks. Use when user requests a new feature, enhancement, or complex change.
Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following best practices.
Create HTML flowcharts and process diagrams with decision trees, color-coded stages, arrows, and swimlanes. Use when users request flowcharts, process diagrams, workflow visualizations, or decision trees.
Plan implementation, design an approach, or create an architecture plan for a Bitwarden iOS feature. Use when asked to "plan implementation", "design approach", "architecture plan", "how should I implement", "what files do I need", or to create a design doc before writing code.
Refine requirements, analyze a ticket, perform gap analysis, or clarify what a Jira/Confluence ticket is asking before coding in Bitwarden iOS. Use when asked to "refine requirements", "analyze ticket", "gap analysis", "clarify ticket", "what does this ticket mean", or to understand scope before implementation begins.
Use when changing a dbt model in a way that could break its consumers — renaming, removing, or retyping a column, or changing a model that downstream models, exposures, dashboards, or BI tools depend on — to judge whether the change is breaking and who it affects. Also use when versioning a model (model versions, latest_version, latest_version_pointer, deprecation_date, migration windows), enforcing contracts, setting access or groups, or doing multi-project dbt Mesh work (cross-project refs via dependencies.yml, disambiguating similarly-named models, splitting a monolith). Covers single- and multi-project, and planning or advising as well as implementing.
| 《图解 Skill —— AI 提效实战指南》专用配图技能。分析本书章节、附录或书稿内容，批量识别需要视觉辅助的位置，并行生成本书统一风格的插图提示词，批量出图，最后回写书稿。 当用户要求"为本书配图"、"给本书章节生成插图"、"补画书中插图"、"重画本书配图"、"生成章节信息图"时使用此技能。 不用于普通文章、营销图、社媒图或其他书籍的通用配图任务。
This skill builds a structured audit trail of an AI-assisted task: what the tool was asked to do, what materials it was given, what it produced, how the output was verified, and what was ultimately relied upon. It documents the workflow for supervision and later review without ruling on privilege or disclosure, so the record stays accurate rather than self-serving.
| Audit de conformité RGPD complet d'un site internet. Réalise une observation systématique du site selon une checklist de 10 sections (mentions légales, hébergeur, formulaires, newsletter, politique de confidentialité, cookies et bandeau, mots de passe, trackers et mesure d'audience, sous-traitants et transferts hors UE, accessibilité du recueil des droits) plus une annexe 22 items reproduisant les exigences des articles 13 et 14 RGPD. Produit un rapport structuré avec niveau de conformité global, points bloquants (risque 3), points de vigilance (risque 2), recommandations prioritaires et notes techniques. automatique (Claude in Chrome, Cowork ou équivalent) ou en mode dégradé copier-coller. "scanne ce site", "audit conformité site", "audite la conformité de [URL]", "audit cookies site", "audit politique de confidentialité site".
>- Produces detailed law-school case briefs of United States judicial opinions in a fixed opinion-by-opinion analysis, five future-application hypotheticals, critique, and verified key quotations. Also builds vote tables, cross-case consistency tables, perspective-based critiques, and LaTeX in article, Beamer and casebook-chapter formats. Use whenever someone asks to brief a case, analyse or explain an opinion, summarise a decision for students, generate hypotheticals from a holding, critique a judgment, tabulate how justices voted, or convert case analysis to LaTeX. Triggers on "brief this case", "case brief", "explain the holding", "what did the court hold", "hypotheticals based on", "critique this opinion", "vote table", "Beamer presentation", "chapter brief", and on any reference to a judicial opinion or Supreme Court decision in a teaching context. Requires web search to verify quotations, votes and holdings.
Build a client instruction schedule — a plain-English, Scott Schedule-style Word table that gathers a struggling client's evidence and instructions issue by issue, with a one-page covering note. Use whenever the user asks for a "client instruction schedule", "instruction schedule", "client questionnaire", "schedule of questions for the client", "get instructions from the client on the papers", or says the client is overwhelmed and needs the case broken into manageable questions. Also trigger when asked to turn case papers into a structured request for client input. Do NOT use for court-facing Scott Schedules, pleadings, witness statements, or advice letters — this skill produces a client-facing working document only. Output is always a .docx draft for solicitor review, never a final document.
Claude skill that turns Claude into a Connecticut-specific divorce planner — nine operating modes from pre-flight intake to post-judgment modification, modeled on Untangle.us's feature surface and grounded in C.G.S. Title 46b, Practice Book Chapter 25, and the 2026-08-01 CCSG schedule. Covers eligibility triage (nonadversarial under § 46b-44a vs standard), financial affidavit (JD-FM-6), child support (JD-FM-220 / CCSG-1 / 1A), alimony (§ 46b-82 fourteen factors), parenting plan (with GAL/AMC escalation under JD-FM-224), settlement agreement (JD-FM-172, TCJA-aware), filing packet (marshal 12-day rule, $360 + $50 fees, JD-FM-75 waiver), and post-judgment motion practice. Hard UPL gate: refuses non-CT, domestic violence (refers CTCADV 1-888-774-2900), hidden assets, courtroom advocacy. Heppner-aware: AI prompts are not privileged. First family-law skill in the Lawvable registry.
Contract intelligence and contract operations workflow skill for Claude and Codex. Guides the full contract lifecycle review process from intake and playbook normalization through clause review, deviation scoring, negotiation planning, approval routing, QA, and action recommendations. Reviews legal, business, operational, compliance, privacy, security, technology, and AI-related risks across contracts and legal documents. Supports NDAs, SaaS agreements, DPAs, procurement contracts, commercial agreements, contract comparisons, redlines, approval packages, clause research, and drafting. Warning-Comprehensive reviews can consume significant Claude/OpenAI tokens, especially for large agreements, playbooks, exhibits, schedules, and multi-document reviews.
U.S. customs and trade-law research assistant for HTS classification, CROSS ruling research, CIT/CAFC decision briefing, duty compilation (General + Special + Chapter 99 + AD/CVD + MPF/HMF), country of origin determination, FTA qualification, and end-to-end import compliance review. Triggers on product classification, tariff questions, customs rulings, trade remedy screening (Section 301/232/201), Partner Government Agency admissibility, and UFLPA forced-labor analysis. Produces attorney-reviewable draft work product with an enforced HTSUS authority hierarchy and explicit evidence ledger.
Audits AI-assisted legal, compliance, governance, and institutional decisions before reliance to determine whether the responsible human or institution has enough access to the evidence, reasoning basis, uncertainty, authority, and review path to genuinely own the decision rather than merely approve, sign, or transmit it.
Analyze any OFAC or OFSI enforcement action — by URL, pasted text, or uploaded document — and produce a structured root cause analysis as a formatted Excel (.xlsx) spreadsheet. Use this skill whenever a user names, links to, pastes, or uploads an OFAC or OFSI enforcement action and asks for any of the following: root cause analysis, compliance gaps, what went wrong, lessons learned, organizational self-assessment, or remediation planning. Also trigger when a user asks \"analyze this enforcement action\", \"what were the root causes\", \"turn this into a checklist\", or \"how do I make sure this doesn't happen to us\". Outputs a single-sheet .xlsx table with six columns: Root Cause | What Went Wrong | How It Went Wrong | What Could Have Stopped It | Is my organization immune to this? (Yes/No/Partial) | Notes.
Depth assessment of whether an AI system is high-risk under Art. 6 of the EU AI Act, grounded in the Commission's draft Art. 6(5) classification guidelines (general principles + Annex I + Annex III). Covers the Annex I product-safety route, all eight Annex III areas with worked examples, the Art. 6(3) exception and its profiling re-exception, and the Art. 25 quasi-provider trap. Outputs a structured decision block, a practitioner memo, and a JSON interchange artefact.
| Maps the full set of legal obligations for the EU AI Act based on role + risk tier, producing an actionable compliance matrix with RACI assignments and implementation priorities. This skill should be used when the user asks to "map AI Act obligations", "check what we need to do under the AI Act", "create a compliance checklist", "check deployer obligations", "assess provider duties", or mentions Art. 26, Art. 16-17, AI literacy Art. 4, DPIA, fundamental rights assessment, or "Pflichtenkatalog" under the AI Act.
Assesses which of the Art. 50(1)-(5) transparency obligations of the EU AI Act apply to a given AI system's provider or deployer, grounded in the final Code of Practice on Transparency of AI-Generated Content (June 2026) and the Commission's draft Art. 50 Guidelines. Covers AI-chatbot disclosure, deepfake and synthetic-content marking/watermarking, emotion-recognition and biometric-categorisation notices, the machine-readable marking duty, the obviousness exceptions, and the implementation timeline. Outputs a formal mini-report plus a per-obligation compliance checklist with gap flags. For breadth-first tier triage use the EU AI Act System Classifier; for raw Art. 50 text and Q&A use the EU AI Act Knowledge Base; for the full role x tier matrix use the EU AI Act Obligations Mapper.
Assess compliance obligations under the EU Data Act (Regulation (EU) 2023/2854) for connected products, IoT devices, data sharing, cloud switching, B2B fairness, B2G data access, dispute resolution, and international data transfers. Covers scope assessment (manufacturer, data holder, data recipient roles), user data access rights, pre-sale transparency, unfair contract terms, public authority data requests, cloud portability, dispute settlement mechanisms, international transfer restrictions, access-by-design obligations, trade secret protection, and cross-regulation mapping with GDPR, AI Act, and CRA. Use when assessing Data Act obligations, designing connected products, drafting data sharing contracts, responding to B2G requests, planning cloud switching capabilities, or evaluating dispute resolution options.
Use this skill when asked to find, cite, analyze, or summarize Icelandic court decisions. Triggers on requests involving Hæstiréttur (Supreme Court), Landsréttur (Court of Appeal), Félagsdómur (Labour Court), héraðsdómur (District Court) case law, or Icelandic legal precedent research.
Turn a lawyer's bounded expertise, workflow, review standard, or legal judgment pattern into a safe, inspectable legal AI skill. Use when a user provides legal memos, comments, checklists, negotiation notes, review habits, compliance playbooks, or professional feedback and wants a reusable Lawve-style skill. Do not impersonate the lawyer or claim to reproduce a person; distill only authorized, source-bounded capability.
Use when a user needs a legal or legal-adjacent Mermaid diagram from a document, pasted text, matter description, process, timeline, party map, obligation map, corporate structure, funds flow, or compliance workflow. Trigger on: "diagram this contract", "visualise this deal/matter", "map the parties", "create a timeline of events", "make an org chart", "obligation checklist", "export as HTML diagram". Not for general-purpose non-legal diagrams, pure graphic design, image generation, or legal advice.
| Helps a lawyer build and use a personalized Legal Guidance Vault — a local folder of structured, privilege-marked entries capturing legal guidance they've given, searchable later by topic, person, or product. Use this skill when the user says "set up my vault," "archive this meeting/email/thread/doc," "log the guidance I gave on [topic]," "save my notes from [meeting]," "what did I say about [topic]," "find the time I advised [person] on [topic]," or "search my vault for [topic]." Runs a setup interview to learn the user's tool stack (meeting notes, calendar, email, docs, messaging, vault location), then generates a customized vault prompt they can reuse in any future Claude session to start archiving and retrieving guidance.
Audits legal AI outputs and workflows for honest compression: unnecessary complexity, false simplicity, excessive caveats, hidden uncertainty and poor cost per legally acceptable output.