Skills.
Give your AI a better way to work.
A skill is a set of written instructions that teaches an AI how to do one job the way it should be done: review a pull request, plan a migration, write the release notes.
Install one here and it travels with your account into Claude, Claude Code, Cursor and every other client you sign in with.
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63,139 results · page 518 of 2,105
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acquirer-red-teamSkillAI & models
Simulate the acquirer's diligence team hunting for reasons to cut your price — their internal red-flags memo with a price-chip estimate per finding. Use when asked to red-team my company before a sale, how will an acquirer attack our valuation, pre-diligence audit, or what will DD find. Produces the
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action-runnerSkillFiles & storage
Turn a skill's recommendations into real, executed actions — open the tickets, file the issues, post the updates — safely: dry-run preview, risk-classified, approval-gated, then recorded back to the brain. Use when asked to act on a plan, file tickets from a checklist, create issues from a PRD, exec
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ad-copySkillAI & models
Write platform-native paid ad copy with multiple angles to test. Use when asked to write ad copy, Google/Facebook/LinkedIn/Instagram ads, PPC headlines, or paid social creative copy. Produces ready-to-ship variants per platform (headlines, primary text, descriptions, CTAs) across distinct angles, si
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aeo-optimizerSkillAI & models
Optimize an article for Answer Engine Optimization (AEO) so AI engines like ChatGPT, Perplexity, and Claude can extract, quote, and cite it. Use when asked to AEO-optimize, make content AI-readable, improve AI citation chances, or adapt an article for answer engines. Produces an AEO-optimised rewrit
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after-the-disasterSkillAI & models
Work through the first hours and days after a disaster — a fire, flood, storm, or evacuation — in the right order: safety and people first, then documenting for insurance and aid, then the immediate recovery steps, without missing the things that cost money or health later. Use when someone says 'my
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agenda-or-cancelSkillProductivity
Enforce the simplest meeting rule that works — no agenda, no meeting — with the three-line agenda format (purpose, decisions sought, pre-reads), the 24-hour rule, and the graceful cancel scripts. Use when asked write an agenda for this meeting, should this meeting happen, our meetings have no agenda
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agent-design-reviewSkillMedia
Review an LLM agent design and find where it will be unreliable, expensive, or unsafe. Use when asked to review an agent architecture, critique a multi-step/tool-using agent, debug an agent that loops or goes off-task, or harden an agent before launch. Produces a structured review — task fit, contro
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agent-era-pricingSkillAI & models
Redesign seat-based pricing for the agent era — when one human runs ten agents, per-seat models collapse. Use when agents are eroding seat counts, when asked to migrate to usage- or outcome-based pricing, to price an agent/API tier, or to defend revenue as customers automate their own usage. Produce
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agent-hiring-panelSkillProductivity
Hire an AI agent the way you'd hire an employee — a role spec with success criteria, a structured work-sample interview run on your real tasks, reference checks (what do actual users report), probation KPIs, and termination criteria written before day one. Use when choosing between AI agents/tools/c
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agent-incident-postmortemSkillMonitoring & ops
Run a blameless postmortem for an incident caused by an AI agent or LLM feature — hallucinated facts shipped to users, runaway tool use, prompt injection, cost blowouts, or wrong actions taken autonomously. Use when asked to write up an AI incident, analyse why an agent did something wrong, or produ
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agent-observability-specSkillMonitoring & ops
Specify the tracing, metrics, and alerting for an AI agent or LLM feature in production. Use when asked what to log for an LLM app, design agent tracing or spans, define quality and cost monitors, or answer 'how do we know if the agent is misbehaving?'. Produces an observability spec with a trace sc
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agent-severanceSkillDocs & knowledge
Offboard an AI agent the way you'd offboard an employee — inventory what it knew and touched, export then purge its memory, revoke every credential and access grant, and write the handover for its successor (human or agent). Use when decommissioning an agent or bot, switching agent vendors, ending a
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agent-specSkillMedia
Specify an autonomous or tool-using AI agent before building it. Use when asked to design an AI agent, define an agent's tools and guardrails, scope what an agent is allowed to do, or write an agent spec/PRD. Produces an agent spec — goal & scope, tools with permissions, the control loop, guardrails
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aging-in-place-assessmentSkillAI & models
Assess whether and how someone can safely stay in their own home as they age — the home hazards, the support gaps, and the modifications and services that make it work. Use when asked can my parent stay in their home safely, aging in place assessment, is it safe for them to live alone, or what do we
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aging-parent-talksSkillAI & models
Prepare the conversations with aging parents that everyone postpones — the driving talk, the money talk, the care-options talk, the moving talk — each with an opener that doesn't ambush, a dignity-first script, rehearsal against realistic resistance, and the fallback when it goes badly. Use when som
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agm-in-a-boxSkillAI & models
Run a club, PTA, or association AGM that finishes on time and holds up later — the notice and agenda done right, a quorum plan, minutes that capture decisions not conversations, elections without awkwardness, and the follow-up that makes decisions real. Use when a volunteer says 'I have to run the A
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ai-agent-reliabilitySkillAI & models
Make an AI agent or automation reliable enough to trust — the tests, checks, and guardrails that catch its failures before they reach anything real. Use when asked how do I test my AI agent, make my automation reliable, my agent works sometimes, or how do I trust an AI workflow in production. Produc
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ai-assisted-performance-reviewSkillAI & models
Evaluate performance fairly when output is AI-assisted — what still measures the human, what now measures the tooling, and how to run the review conversation. Use when reviewing someone whose work is heavily AI-assisted, when output volume stopped meaning anything, when calibrating a team with uneve
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ai-code-reviewSkillSecurity
Review AI-authored code for its characteristic failure modes — plausible-but-wrong logic, hallucinated APIs, over-engineering, dead scaffolding, and silent security shortcuts. Use when reviewing an AI-generated or heavily AI-assisted PR, when AI-written code keeps shipping subtle bugs, or when setti
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ai-content-auditSkillSearch
Audit a content library, docs site, or blog for AI-generated filler that's eroding trust and search performance — and triage what to fix, rewrite, or delete. Use when asked to find slop in a content library, audit AI-written content quality, explain why content engagement or rankings dropped after s
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ai-context-primerSkillProductivity
Build the context an AI needs to do a task well — the background, constraints, examples, and format it can't guess — so you get a great result on the first try instead of a generic one you have to keep correcting. Use when asked why does AI give me generic answers, how do I give AI better context, m
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ai-disclosure-policySkillAI & models
Decide when and how your product and communications must (or should) label AI-generated content, and write the disclosure policy — surface-by-surface rules, exact label wording, and the review trigger for regulations like the EU AI Act's transparency obligations. Use when asked 'do we have to label
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ai-ethics-reviewSkillCloud & infra
Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, priva
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ai-eval-planSkillDatabases & data
Design an evaluation plan for an LLM or AI feature before shipping it. Use when asked how to evaluate a prompt/model/agent, set up an eval harness, define quality metrics for an AI feature, or build a regression gate. Produces an eval plan — task definition, datasets, metrics & rubrics, baselines, a
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ai-feature-prdSkillAI & models
Write a PRD for an AI-powered feature, covering the things normal PRDs miss. Use when asked to spec an AI/LLM feature, write a PRD for a feature that uses a model, or plan an AI capability (assistant, summarizer, generator, classifier). Produces an AI feature PRD — problem & UX of uncertainty, model
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ai-output-verifierSkillAI & models
Check AI output before you trust or use it — where it's likely wrong, what to verify, and how to catch confident-sounding errors. Use when asked can I trust this AI answer, how do I verify what AI told me, fact-check this AI output, or is this AI response reliable. Produces a risk read on the specif
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ai-product-canvasSkillAI & models
Structure AI and ML product decisions with the rigour of any product decision. Use when building AI-powered features, evaluating LLM integrations, designing AI products, or assessing AI readiness. Produces a complete AI product canvas covering problem definition, model approach, data requirements, e
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ai-roi-auditSkillAI & models
Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produce
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ai-tool-pickerSkillMedia
Figure out which AI tool actually fits the task in front of you — chatbot, coding assistant, image model, agent, or none — instead of forcing one tool onto everything. Use when asked which AI tool should I use for, what's the best AI for, do I even need AI for this, or should I use ChatGPT or someth
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ai-usage-policySkillAI & models
Write an AI usage policy people can actually follow — approved tools, data rules, disclosure duties, and review obligations, in one page instead of legal fog. Use when asked for a company AI policy, acceptable-use rules for ChatGPT/Claude/Copilot at work, guidance on what data may go into AI tools,
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What is a skill?
A skill is plain text, usually a SKILL.md file and the scripts it refers to, written for an AI rather than for a person. It carries the steps, the house rules and the examples a good answer needs, so you stop pasting the same briefing into every new chat.
63,068 of the 63,139 skills listed here can be served through ahel today, and they come from public repositories. Each one has its own page with the instructions themselves on it, so you can read what a skill will tell your AI to do before you install it.
Install one and every AI you use gets it
Installing a skill adds it to your workspace and turns it on in the same step. Claude Code surfaces it as a slash command; any client can read the full instructions with the skill_read tool.
Nothing is copied into a project folder. The instructions are served from your account, so the same skill is there in every AI you connect, and turning it off removes it from all of them at once.