tk-deep-research

Skill: deep-research-core — TricorderKit v0.7

Local-first autonomous research: collect, deduplicate, score and synthesize.

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Triggers

/tk:deep-research "<query>"
/tk:deep-research --pipeline content "<query>"
/tk:deep-research --pipeline github "<query>"
/tk:deep-research --dry-run "<query>"

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Agent instructions

Research algorithm

1. Identify the pipeline based on the query (content / entity / github / vendor)
2. Read sources/trusted_sources.yml → select relevant sources
3. Block any source in blocked_sources.yml
4. Collect in parallel (max 3 simultaneous sources)
5. Deduplicate by title hash + semantic similarity (threshold 0.85)
6. Score each result (0.0 → 1.0) according to scoring_weights
7. Filter: keep score >= 0.70 only
8. Synthesize in structured Markdown
9. Index in Obsidian (target folder per pipeline)
10. Index in Qdrant if available
11. Return final report with cited sources

Important rules

• Never use a source outside trusted_sources.yml
• Always cite sources in the final report
• Limit to 500 tokens per item in synthesis (atomic principle)
• If Qdrant down → continue without vector indexing (degraded mode)
• Log in .planning/DECISIONS.md if research leads to a decision

Available pipelines (adapt to your domain)

Pipeline	Usage
content	Domain content watch, entity profiles
entity	Authors, publishers, producers
github	Repo audits, integration scoring
vendor	VPS, services, comparisons

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Output format

{
  "status": "success",
  "skill_name": "tk-deep-research",
  "query": "<query>",
  "pipeline": "<pipeline>",
  "items_found": N,
  "items_after_dedup": N,
  "items_above_threshold": N,
  "report_path": "vault/reports/research_YYYY-MM-DD_<slug>.md",
  "output": {
    "summary": "...",
    "data": [],
    "sources_used": []
  }
}

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Degraded mode

• Qdrant down → skip vector indexing, continue
• Obsidian inaccessible → save to vault/reports/ locally
• Source API down → use SQLite cache if available