requirements-analysis
Guides discovery of real needs and constraints. Helps identify problems in requirements.
Your agent can do more. Find the skill that makes it happen.
Find your next superpower If you are an agent, refer to our llms.txt for full access.Guides discovery of real needs and constraints. Helps identify problems in requirements.
Investigate a question against high-trust primary sources and capture the findings as a cited Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to an isolated agent.
Investigates uncertainty by tracing code or testing a recurring pattern. Produces an evidence-backed answer to one cited question.
Use the /research skill when performing background research from the literature or the web to create a RESEARCH.md file; also covers use of deep-research-client
Investigates topics and gathers documentation or API facts from high-trust primary sources. Captures findings in repository Markdown files.
Investigates topics against high-trust primary sources and saves findings as Markdown in the repository. Covers documentation and API fact gathering, including research delegated to a background agent.
Investigates topics, collects documentation or API facts, and checks findings against highly credible primary sources. Saves results as Markdown in the repository and supports delegating reading to background agents.
Uses one or more subagents to investigate many files, long logs, large diffs, or broad codebase questions. Distills findings about behavior, usage, root causes, or PRs while keeping investigation noise out of the orchestrator's context.
Systematic web and codebase research workflow for information queries and fact verification. Gathers authoritative sources, executes query chains, evaluates evidence, and synthesizes grounded answers with inline citations.
Turns interviews, notes, support tickets, surveys, and product context into an evidence-backed HTML artifact. Includes an evidence ledger, theme map, confidence heatmap, opportunity matrix, decision memo, and experiment queue to support product and design decisions while preserving uncertainty.
Focuses on academic research engineering with scientific rigor and objective criticism. Emphasizes theoretical correctness, formal verification, and optimal implementation across required technologies.
Gathers research materials from clustering results, user keywords, or domain descriptions. Produces structured resource lists for each domain, supporting systematic literature and patent collection after domain mapping.
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Copy the install command from a skill page and run it in your project.
npx skillycli add owner/repo --skill name