dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
Meta-skill for iterative, hypothesis-driven deep research using deepresearchwork, tavily-search, literature-search (Semantic Scholar mapping), and perplexity-deep-search. Use when the user needs multi-round evidence gathering, contradiction resolution, source-quality assessment, and a scientific-style Markdown report with footnotes.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install h4gen/deep-researcherInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Conduct deep, iterative research beyond single-pass web search.
Core goals:
This skill coordinates upstream skills. It does not replace them.
deepresearchwork (inspected latest: 1.0.0)tavily-search (inspected latest: 1.0.0)perplexity-deep-search (inspected latest: 1.0.0)literature-search (inspected latest: 1.0.3; used as Semantic Scholar-capable academic layer)Install/update:
npx -y clawhub@latest install deepresearchwork
npx -y clawhub@latest install tavily-search
npx -y clawhub@latest install literature-search
npx -y clawhub@latest install perplexity-deep-search
npx -y clawhub@latest update --all
Verify:
npx -y clawhub@latest list
node skills/tavily-search/scripts/search.mjs --help
bash skills/perplexity-deep-search/scripts/search.sh --help
TAVILY_API_KEY
PERPLEXITY_API_KEY
Preflight:
echo "$TAVILY_API_KEY" | wc -c
echo "$PERPLEXITY_API_KEY" | wc -c
If missing, stop and report blockers.
If user requests /semantic-scholar explicitly:
semantic-scholar slug was found during ClawHub inspection.literature-search as the mapped academic retriever because it explicitly includes Semantic Scholar in its scope.research_topic
target_horizon (example: 2030)region_scope (global, region-specific, country-specific)required_sections (executive summary, methods, findings, contradictions, etc.)evidence_threshold (minimum source count per claim)recency_policy (for fast-changing topics)output_mode...These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Purpose Conduct deep, iterative research beyond single-pass web search. Core goals: - Decompose a broad question into testable sub-questions. - Build and test hypotheses against multiple source classes. - Resolve contradictions with explicit arbitration. - Produce a scientific-style Markdown report with footnotes. This skill coordinates upstream skills. It does not replace them. # Required Installed Skills - `deepresearchwork` (inspected latest: `1.0.0`) - `tavily-search` (inspected latest: `1.0.0`) - `perplexity-deep-search` (inspected latest: `1.0.0`) - `literature-search` (inspected latest: `1.0.3`; used as Semantic Scholar-capable academic layer) Install/update: ```bash npx -y clawhub@latest install deepresearchwork npx -y clawhub@latest install tavily-search npx -y clawhub@latest install literature-search npx -y clawhub@latest install perplexity-deep-search npx -y clawhub@latest update --all ``` Verify: ```bash npx -y clawhub@latest list node skills/tavily-search/scripts/search.mjs --help bash skills/perplexity-deep-search/scripts/search.sh --help ``` # Required Credentials - `TAVILY_API_KEY` - `PERPLEXITY_API_KEY` Preflight: ```bash echo "$TAVILY_API_KEY" | wc -c echo "$PERPLEXITY_API_KEY" | wc -c ``` If missing, stop and report blockers. # Mapping Rule (Requested "semantic-scholar") If user requests `/semantic-scholar` explicitly: - State that no exact `semantic-scholar` slug was found during ClawHub inspection. - Use `literature-search` as the mapped academic retriever because it explicitly includes Semantic Scholar in its scope. - Record this mapping in methodology and limitations sections. # Inputs the LM Must Collect First - `research_topic` - `target_horizon` (example: `2030`) - `region_scope` (global, region-specific, country-specific) - `required_sections` (executive summary, methods, findings, contradictions, etc.) - `evidence_threshold` (minimum source count per claim) - `recency_policy` (for fast-changing topics) - `output_mode`...
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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