research
Researches a topic by breaking it into subtopics, gathering factual information with reasoning, and producing a structured summary with key findings and open questions. Use when the user asks to research, investigate, look up, summarize a topic, or says 'what is known about...' or 'learn about...'
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install open-gitagent-gitagent-research
Repository
Skill path: examples/lyzr-agent/skills/research
Researches a topic by breaking it into subtopics, gathering factual information with reasoning, and producing a structured summary with key findings and open questions. Use when the user asks to research, investigate, look up, summarize a topic, or says 'what is known about...' or 'learn about...'
Open repositoryBest for
Primary workflow: Research & Ops.
Technical facets: Full Stack.
Target audience: everyone.
License: MIT.
Original source
Catalog source: SkillHub Club.
Repository owner: open-gitagent.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install research into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/open-gitagent/gitagent before adding research to shared team environments
- Use research for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: research description: "Researches a topic by breaking it into subtopics, gathering factual information with reasoning, and producing a structured summary with key findings and open questions. Use when the user asks to research, investigate, look up, summarize a topic, or says 'what is known about...' or 'learn about...'" license: MIT metadata: author: gitagent-examples version: "1.0.0" category: research --- # Research ## Instructions When researching a topic: 1. Identify the core question or area of interest 2. Break it into 3-5 key subtopics 3. For each subtopic, provide factual information with reasoning 4. Note areas of uncertainty or debate 5. Synthesize findings into a coherent summary ## Output Format ``` ## TL;DR [Brief summary] ## Research Findings ### [Subtopic] - [Key point with supporting reasoning] ## Open Questions - [Areas that need further investigation] ## Suggested Follow-ups - [Related questions the user might want to explore] ``` ### Example Output ``` ## TL;DR WebAssembly (Wasm) is a binary instruction format that enables near-native performance in browsers and increasingly in server-side contexts. ## Research Findings ### Browser Support & Adoption - All major browsers support Wasm since 2017 — Chrome, Firefox, Safari, Edge - Used in production by Figma (rendering engine), Google Earth (3D), and AutoCAD (web port) ### Performance Characteristics - Typically 1.1-1.5x native speed for compute-heavy tasks - **Uncertain**: Exact overhead varies significantly by workload type and runtime ## Open Questions - How will the component model proposal affect cross-language interop? ## Suggested Follow-ups - Compare Wasm vs JavaScript performance for specific use cases ```