
Dossier Collect
- 610 installs
- 67k repo stars
- Updated August 4, 2026
- ruvnet/ruflo
dossier-collect is a Claude agent skill that builds a graph-structured dossier on a seed entity via parallel fan-out and recursive expansion across six intelligence sources for developers who need unified research before
About
dossier-collect is a skill in ruvnet/ruflo that constructs a graph-structured dossier on a seed entity using parallel fan-out and recursive expansion. It fans out across six source classes—web, memory, knowledge-graph, codebase, ADR index, and git intel—and accepts CLI flags such as --max-depth, --max-breadth, --sources, --budget-usd, and --exact to cap traversal and spend. The skill integrates claude-flow MCP tools for memory_store, memory_search, agentdb pattern search, embeddings_search, and hooks intelligence pattern retrieval. Reach for dossier-collect when onboarding to an unfamiliar codebase, investigating a person or organization, or assembling ADR and git context before architecture or implementation work. The output is a connected dossier graph rather than isolated search hits, making it suited to agent workflows that must reason across heterogeneous evidence.
- dossier-collect
Dossier Collect by the numbers
- 610 all-time installs (skills.sh)
- +6 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #641 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 610 |
|---|---|
| repo stars | ★ 67k |
| Last updated | August 4, 2026 |
| Repository | ruvnet/ruflo ↗ |
How do you build a research dossier across codebase and web?
Use dossier-collect for development tasks
Who is it for?
Developers or agents investigating a seed entity who need recursive, budget-capped intelligence across web, memory, codebase, ADR, and git sources.
Skip if: Developers who only need a single-file grep or one API lookup without cross-source graph assembly.
When should I use this skill?
A task requires deep entity research spanning web, institutional memory, knowledge graphs, codebase files, ADRs, and git history with controlled depth and cost.
What you get
Graph-structured dossier with linked entities, source citations, and depth-breadth-controlled expansion paths.
- Graph-structured entity dossier
- Cross-source relationship map
By the numbers
- Queries 6 intelligence source types: web, memory, knowledge-graph, codebase, ADR index, and git intel
Files
Dossier Collect
Recursive parallel investigation that builds a graph-structured dossier on a seed entity.
When to use
You have a seed (a username, file, symbol, ADR-id, URL, or concept) and want to expand outward discovering every connected entity, with provenance per claim — rather than answering a specific question.
For specific questions use deep-research. For multi-step plans use goal-plan.
Steps
1. Detect seed type — classify as one of: username (handle), file (path), symbol (code identifier), adr (ADR-NNN), url, or concept (free text). 2. Pick sources — match the source matrix to the seed type. Default: all applicable. 3. Start trajectory — call mcp__claude-flow__hooks_intelligence_trajectory-start with task dossier:<slug>. 4. Round 0 fan-out — issue ALL source queries in ONE message. Examples:
- For
username:WebSearch,WebFetchon github.com/<user>,mcp__claude-flow__memory_search_unified - For
adr:ReadADR file,Grepreferences,mcp__claude-flow__memory_searchnamespaceadr - For
symbol:Grep,Glob,mcp__claude-flow__embeddings_search
5. Extract entities — from each hit, surface entities (people, repos, files, adrs, urls, terms). Lightweight regex + heuristics; no LLM extraction unless ambiguous. 6. De-dup — drop entities already in the dossier. If --exact is unset, also drop entities whose embedding cosine similarity ≥ 0.92 to an existing node. 7. Round k recursion — for each new entity (capped at --max-breadth per source), recurse to step 4 until depth ≥ --max-depth OR budget exhausted. 8. Aggregate — build { nodes, edges } graph. Each node carries { id, type, attrs, sources: [...] }. Each edge carries { from, to, kind, source, confidence }. 9. Render artifacts:
<slug>.md— executive summary, entity table, mermaid graph, source-provenance footnotes<slug>.json— machine-readable graph- Default location:
v3/docs/examples/dossiers/<slug>/
10. Persist — mcp__claude-flow__memory_store namespace dossier key <slug>. 11. End trajectory — mcp__claude-flow__hooks_intelligence_trajectory-end with success status.
Output schema (JSON)
{
"seed": "ruvnet",
"seedType": "username",
"depth": 2,
"truncated": false,
"generatedAt": "ISO-8601",
"nodes": [
{ "id": "ruvnet", "type": "username", "attrs": { "...": "..." }, "sources": ["WebSearch", "github.com"] }
],
"edges": [
{ "from": "ruvnet", "to": "ruflo", "kind": "owns", "source": "github.com", "confidence": "high" }
],
"stats": { "nodesByType": {}, "sourcesUsed": [], "tokensSpent": 0 }
}Budget discipline
- If
--budget-usdis set, track approximate cost via trajectory. On exhaustion: emit partial dossier withtruncated: trueand the entities still queued. - BFS expansion only — finish round k before round k+1.
- Never silently truncate. Always mark and record what was skipped.
Examples
/ruflo-goals:dossier-collect ruvnet
/ruflo-goals:dossier-collect ADR-097 --max-depth 1
/ruflo-goals:dossier-collect "src/memory/hnsw.ts" --sources codebase,git,memory
/ruflo-goals:dossier-collect "ruflo-goals" --max-breadth 5 --budget-usd 1Related skills
How it compares
Pick dossier-collect over single-source search skills when you need a connected graph dossier across memory, codebase, ADRs, and git rather than one-off web results.
FAQ
What sources does dossier-collect query?
dossier-collect fans out across web, memory, knowledge-graph, codebase, ADR index, and git intel. Developers can limit sources with --sources and cap traversal using --max-depth, --max-breadth, and --budget-usd flags on the seed entity.
How does dossier-collect control research cost?
dossier-collect accepts --budget-usd alongside --max-depth and --max-breadth to bound recursive expansion spend. The --exact flag and --sources filter further narrow which intelligence channels participate in the graph build.