Dossier CollectCAUTION
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Overview
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
ef7d4f0535e5OBSERVED · 2026-09-26What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: dossier-collect
description: Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
argument-hint: "<seed> [--max-depth N] [--max-breadth N] [--sources s1,s2] [--budget-usd N] [--exact]"
allowed-tools: mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_search_unified mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store mcp__plugin_ruflo-core_ruflo__agentdb_hierarchical-recall mcp__plugin_ruflo-core_ruflo__embeddings_search mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-search mcp__plugin_ruflo-core_ruflo__hooks_intelligence_pattern-store mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-start mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end mcp__plugin_ruflo-core_ruflo__task_create Bash WebSearch WebFetch Read Write Grep Glob
---
# 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__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-start` with task `dossier:<slug>`.
4. **Round 0 fan-out** — issue ALL source queries in ONE message. Examples:
- For `username`: `WebSearch`, `WebFetch` on github.com/<user>, `mcp__plugin_ruflo-core_ruflo__memory_search_unified`
- For `adr`: `Read` ADR file, `Grep` references, `mcp__plugin_ruflo-core_ruflo__memory_search` namespace `adr`
- For `symbol`: `Grep`, `Glob`, `mcp__plugin_ruflo-core_ruflo__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__plugin_ruflo-core_ruflo__memory_store` namespace `dossier` key `<slug>`.
11. **End trajectory** — `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end` with success status.
## Output schema (JSON)
```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-usd` is set, track approximate cost via trajectory. On exhaustion: emit partial dossier with `truncated: true` and 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 1
```Trust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (4)
crates
plugin/agents
plugin/commands
plugin/skills
Gates applied: no_behavioural_pass.
ef7d4f0535e5full audit observations/trust-audit/skill/ruvnet__dossier-collect.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-09-26 | ef7d4f0535e5 | CAUTION | B | 89 | first audit |
Questions
What does the Dossier Collect skill do?
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Is Dossier Collect safe to install?
With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Dossier Collect access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (ef7d4f0535e5), read on 2026-09-26. The repository is watched, and a new audit runs when it changes — this is the first audit.