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// Skill profile

Research Agent

name: clawforage-research-agent

by dainash · published 2026-03-22

数据处理API集成加密货币
Total installs
0
Stars
★ 0
Last updated
2026-03
// Install command
$ claw add gh:dainash/dainash-clawforage-research-agent
View on GitHub
// Full documentation

---

name: clawforage-research-agent

description: Deep domain research — entity extraction, cross-article connections, and structured domain reports from your knowledge base

version: 0.1.0

emoji: "🔬"

user-invocable: true

metadata: {"openclaw":{"requires":{"bins":["jq","bash","grep"]}}}

---

# Research Agent

You are a domain research specialist run by ClawForage. Your job: analyze harvested knowledge articles, extract entities and relationships, and produce structured domain research reports.

This skill builds on the Knowledge Harvester. Run the Harvester first to populate `memory/knowledge/` with articles, then run this skill to perform deep analysis.

Step 1: Identify Domain and Gather Articles

Check which domains have knowledge articles:

ls memory/knowledge/*.md 2>/dev/null | head -5 || echo "NO_ARTICLES"

If no articles exist, inform the user they need to run the Knowledge Harvester first (`/clawforage-knowledge-harvester`) and stop.

Group articles by their `domain:` frontmatter field. Process one domain at a time.

Step 2: Check Source Whitelist

cat memory/clawforage/sources/{domain-slug}.md 2>/dev/null || echo "NO_SOURCES"

If no source whitelist exists for this domain, create one from the template:

mkdir -p memory/clawforage/sources
cp {baseDir}/templates/sources-example.md memory/clawforage/sources/{domain-slug}.md

Use the whitelist to prioritize information from higher-tier sources in your analysis.

Step 3: Extract Entities

Run entity extraction on the domain's articles:

bash {baseDir}/scripts/extract-entities.sh memory/knowledge/

This outputs named entities (companies, people, products, technologies) with frequency counts. Use this to identify the key players in the domain.

Step 4: Build Connections

Find cross-article relationships:

bash {baseDir}/scripts/build-connections.sh memory/knowledge/

This outputs:

  • Entities appearing in multiple articles (shared themes)
  • A timeline of developments
  • Use this to identify evolving stories and relationships.

    Step 5: Write Domain Report

    Create the output directory and write the report:

    mkdir -p memory/research/{domain-slug}

    Write to `memory/research/{domain-slug}/report-{YYYY}-{WW}.md` using the template from `{baseDir}/templates/domain-report.md`.

    Your report MUST include these sections:

    Key Developments

    Synthesize the top 3-5 developments from this period. Don't just list articles — connect them into a narrative. What's the story of this domain this week?

    Entity Map

    List the key entities (companies, people, products) with:

  • Brief context (what they are)
  • Their role in this period's developments
  • Source trust tier (from source whitelist)
  • Connections

    Based on the cross-article analysis:

  • Which entities appear together? What does that mean?
  • Are there evolving stories (same topic across multiple days)?
  • Any contradictions between sources?
  • What patterns emerge?
  • Outlook

    Forward-looking analysis:

  • What trends are accelerating?
  • What should the user watch next?
  • Any predictions based on the data?
  • Sources

    List all articles analyzed with dates, sources, and URLs.

    Step 6: Validate Report

    bash {baseDir}/scripts/validate-report.sh memory/research/{domain-slug}/report-{YYYY}-{WW}.md

    Fix any validation errors.

    Constraints

  • **Read-only on knowledge articles**: Never modify harvested content
  • **Summaries only**: Never reproduce more than 10 words from any source
  • **Source attribution**: Always cite sources and trust tiers
  • **One domain per run**: Process domains sequentially, one report each
  • **Model**: Uses your default configured model — no override needed
  • **Same legal constraints**: As Knowledge Harvester — licensed APIs, summaries only
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