Skills

The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.

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Skills

5

Categories

9

Compatible tools

4

Contributors

2

Showing 15 of 5 skills

Grant Proposal Writeradvanced

Helps researchers and nonprofits draft compelling grant proposals. Structures the significance, aims, methodology, timeline, and budget justification to match a funder's priorities and review criteria, tightens the narrative, and flags gaps a reviewer would penalize before submission.

3 models
Contract Analysisadvanced

Analyzes legal and business contracts to extract key terms, identify risks, compare clauses against standard templates, and generate summaries. Highlights unusual provisions, missing protections, and negotiation points. Supports NDAs, SaaS agreements, employment contracts, and vendor agreements.

3 models
ASO Competitor Analysisadvanced

Performs a comprehensive competitive intelligence analysis for mobile apps on the App Store and Google Play. Compares metadata, keyword gaps, creative strategy (screenshots, preview video, icon), ratings, monetization, and growth signals across up to 5 competitors, then delivers a prioritized opportunity map with quick wins and strategic recommendations.

3 models
Literature Reviewadvanced

Conducts systematic literature reviews across scientific databases including PubMed, arXiv, bioRxiv, and Semantic Scholar. Synthesizes findings from multiple papers, identifies research gaps, maps citation networks, and produces structured review documents suitable for grant proposals or publication introductions.

3 models
Hypothesis Generationadvanced

Assists researchers in generating, refining, and evaluating scientific hypotheses. Analyzes existing literature and data to propose testable hypotheses, identifies confounding variables, suggests experimental designs, and evaluates feasibility. Supports structured frameworks like PICO for clinical research and helps formulate null/alternative hypotheses with appropriate statistical tests.

3 models

Skills vs MCP servers

what's the difference?

Skillsthe “what to do”

A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.

MCP serversthe “how to connect”

An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. MCP adds connections and actions, not task instructions.

Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.

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