Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
12
Categories
9
Compatible tools
4
Contributors
2
Showing 1–12 of 12 skills
Reviews claims in a document for accuracy and verifiability. Extracts discrete factual statements, rates each as supported, unsupported, or needs-verification, flags logical inconsistencies and unsourced numbers, and suggests what evidence would confirm or refute each claim. Designed to reduce hallucinated or outdated facts before publishing.
Designs surveys that produce reliable, unbiased data. Turns research goals into clear questions, chooses appropriate scales and response types, avoids leading and double-barreled wording, orders questions to reduce bias, and plans screening and branching logic. Outputs a ready-to-field questionnaire with an analysis plan for each question.
Builds discovery and usability interview guides that surface real insight. Translates research questions into open, non-leading prompts, sequences warm-up to deep-dive topics, adds follow-up probes, and applies techniques like the "five whys" and past-behavior questions. Outputs a timed guide with a consent intro and a synthesis template for notes.
Builds structured competitive analyses from public information. Maps competitors across positioning, pricing, features, target segments, and go-to-market motion; produces feature-comparison matrices and SWOT summaries; and highlights differentiation gaps and opportunities. Emphasizes citing sources and separating verified facts from inference.
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.
Conducts structured market and competitor research and turns it into a decision-ready brief. Covers market sizing (TAM/SAM/SOM), competitor feature and pricing matrices, positioning and differentiation, customer segments, and SWOT, with clearly stated assumptions and sources so conclusions can be traced and challenged.
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.
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.
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.
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.
Summarizes web pages, PDFs, articles, and documents into concise, structured summaries. Extracts key points, main arguments, data, and conclusions. Supports multiple output formats including bullet points, executive summaries, and structured notes with citations.
Summarizes research papers, technical articles, and documentation into structured briefs. Extracts key findings, methodology, limitations, and practical implications. Adapts output format from executive summary to detailed technical breakdown.
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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