How do I install the Research Agent skill?

Run npx skillmds@latest add thewatcher01/research-agent in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Research Agent safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Research Agent?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Research Agent free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Research Agent?

TheWatcher01 (@thewatcher01) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Research Agent by thewatcher01 — Agent Skill

Name: Research Agent
Rating: 4.2 (5 reviews)
Author: TheWatcher01

Research Agent

Systematic deep research methodology using multiple sources. USE when: researching SOTA techniques, comparing libraries/frameworks, finding best practices, verifying claims, investigating bugs via GitHub issues, technical due diligence, literature review. Trigger: "research X", "find the best way to Y", "what's the SOTA for Z", "compare A vs B", "is X still maintained". Combines web, GitHub, docs and codebase sources.

TheWatcher01 264a15d 3.8 KB Updated Sep 10, 2026

File contents

Skill: Research Agent

Research Protocol

Step 1: Decompose the query

Query: "best free LLM for code generation 2026"

Decompose into:
- What: free LLMs (no cost inference)
- Domain: code generation (function, debug, complete)
- Constraint: 2026 (recent, not outdated)
- Implicit: API vs local, speed vs quality

Step 2: Source hierarchy (search in parallel)

Priority	Source	Tool	What to look for
1	Codebase	semantic_search, grep	Existing patterns, prior art
2	Official docs	fetch_webpage	Latest API, breaking changes
3	GitHub	fetch_webpage issues/discussions	Known bugs, community solutions
4	Community	fetch_webpage (SO, Reddit, Discord)	Real-world experiences
5	Registries	npm/PyPI/crates.io	Popularity, maintenance status

Step 3: Validate findings

Validation checklist:

Date check: is this < 6 months old? If not, verify still valid
Version check: compatible with project's pinned versions?
Cross-reference: confirmed by ≥ 2 independent sources?
Author credibility: official docs > known experts > anonymous posts

Step 4: Synthesize

Structure output as:
1. TL;DR (1 sentence answer)
2. Recommendation (with rationale)
3. Key findings (3-5 bullet points)
4. Trade-offs (pros/cons table)
5. Sources (cited with date)
6. Next steps (actionable)

Research Templates

Technology comparison

Compare [A] vs [B] for [use case]:

| Criteria | A | B |
|----------|---|---|
| Performance | | |
| Cost | | |
| Community | | |
| Maintenance | | |
| License | | |
| Learning curve | | |

Recommendation: [A/B] because [reason]

SOTA research

SOTA for [topic] as of [date]:

State of the art:
- Best approach: [name] — [why]
- Performance benchmark: [metric] = [value]
- Key paper: [authors, venue, year]
- Production-ready implementation: [repo/package]

Recent game changers:
- [paper/technique]: changes [what] by [how much]

What's still open:
- [challenge 1]
- [challenge 2]

GitHub issue investigation

Bug: [description]

Search: GitHub issues → repo/issues?q=[keywords]

Findings:
- Issue #[N]: [title] — Status: [open/closed/PR merged]
- Fix: [commit/PR link]
- Workaround: [if applicable]

Root cause: [explanation]
Solution: [steps]

Query Optimization for AI Research

Use these search patterns for better results:

# Web search — specific and recent
"[technology] [problem] site:github.com 2025"
"[library] best practices [year]"
"[error message] fix [language]"

# GitHub issues
"repo:[owner/repo] [keyword] is:issue"
"[error] in:title is:closed"

# Docs
"[library] [version] [feature] docs"

Anti-Patterns in Research

❌ Trust first result only → ✅ Cross-reference 3+ sources
❌ Use outdated tutorials (2020-2022 for fast-moving domains) → ✅ Check dates
❌ Skip official docs → ✅ Official docs first for API accuracy
❌ Research without codebase check → ✅ Check existing patterns first
❌ Deep research for simple facts → ✅ Match depth to complexity

ZeroClaw Integration

# Trigger deep research SOP
zeroclaw agent -m "hint:smart research: what's the best free embedding model for RAG in 2026?"

# Research + store in memory
zeroclaw agent -m "research zeroclaw provider rotation patterns and save findings to memory"

---name: research-agentdescription: Systematic deep research methodology using multiple sources. USE when: researching SOTA techniques, comparing libraries/frameworks, finding best practices, verifying claims, investigating bugs via GitHub issues, technical due diligence, literature review. Trigger: "research X", "find the best way to Y", "what's the SOTA for Z", "compare A vs B", "is X still maintained". Combines web, GitHub, docs and codebase sources.---# Skill: Research Agent## Research Protocol### Step 1: Decompose the query```Query: "best free LLM for code generation 2026"Decompose into:- What: free LLMs (no cost inference)- Domain: code generation (function, debug, complete)- Constraint: 2026 (recent, not outdated)- Implicit: API vs local, speed vs quality```### Step 2: Source hierarchy (search in parallel)| Priority | Source | Tool | What to look for ||----------|--------|------|-----------------|| 1 | Codebase | semantic_search, grep | Existing patterns, prior art || 2 | Official docs | fetch_webpage | Latest API, breaking changes || 3 | GitHub | fetch_webpage issues/discussions | Known bugs, community solutions || 4 | Community | fetch_webpage (SO, Reddit, Discord) | Real-world experiences || 5 | Registries | npm/PyPI/crates.io | Popularity, maintenance status |### Step 3: Validate findingsValidation checklist:- [ ] Date check: is this < 6 months old? If not, verify still valid- [ ] Version check: compatible with project's pinned versions?- [ ] Cross-reference: confirmed by ≥ 2 independent sources?- [ ] Author credibility: official docs > known experts > anonymous posts### Step 4: Synthesize```Structure output as:1. TL;DR (1 sentence answer)2. Recommendation (with rationale)3. Key findings (3-5 bullet points)4. Trade-offs (pros/cons table)5. Sources (cited with date)6. Next steps (actionable)```## Research Templates### Technology comparison```Compare [A] vs [B] for [use case]:| Criteria | A | B ||----------|---|---|| Performance | | || Cost | | || Community | | || Maintenance | | || License | | || Learning curve | | |Recommendation: [A/B] because [reason]```### SOTA research```SOTA for [topic] as of [date]:State of the art:- Best approach: [name] — [why]- Performance benchmark: [metric] = [value]- Key paper: [authors, venue, year]- Production-ready implementation: [repo/package]Recent game changers:- [paper/technique]: changes [what] by [how much]What's still open:- [challenge 1]- [challenge 2]```### GitHub issue investigation```Bug: [description]Search: GitHub issues → repo/issues?q=[keywords]Findings:- Issue #[N]: [title] — Status: [open/closed/PR merged]- Fix: [commit/PR link]- Workaround: [if applicable]Root cause: [explanation]Solution: [steps]```## Query Optimization for AI ResearchUse these search patterns for better results:```bash# Web search — specific and recent"[technology] [problem] site:github.com 2025""[library] best practices [year]""[error message] fix [language]"# GitHub issues"repo:[owner/repo] [keyword] is:issue""[error] in:title is:closed"# Docs"[library] [version] [feature] docs"```## Anti-Patterns in Research- ❌ Trust first result only → ✅ Cross-reference 3+ sources- ❌ Use outdated tutorials (2020-2022 for fast-moving domains) → ✅ Check dates- ❌ Skip official docs → ✅ Official docs first for API accuracy- ❌ Research without codebase check → ✅ Check existing patterns first- ❌ Deep research for simple facts → ✅ Match depth to complexity## ZeroClaw Integration```bash# Trigger deep research SOPzeroclaw agent -m "hint:smart research: what's the best free embedding model for RAG in 2026?"# Research + store in memoryzeroclaw agent -m "research zeroclaw provider rotation patterns and save findings to memory"```

Frequently asked questions