research-orchestration

name	research-orchestration
description	Agents should invoke this skill for broad multi-claim research projects needing planning, parallel investigation, source merging, gap closure, citation audit, and final synthesis when narrower research skills are insufficient.

Research orchestration

Single workflow entry point for end-to-end investigations. Detailed rules live in workspace-researcher/AGENTS.md (task class, parallel investigation, Deep Research Protocol, citation audit); this skill is the ordered checklist for executing them.

When to use

• Broad question with several independent sub-questions or claim clusters.
• Mixed sources (web + docs + papers) and one final report or contract output.
• User or delegating agent asked for deep research without pointing at a single comparison or single paper.

Prefer tech-deep-dive, competitor-analysis, or paper-summarizer when the task clearly matches one of those shapes.

Pipeline

1. Classify depth — Quick / standard / deep (AGENTS.md task-class table). Honor explicit quick / standard / deep or /deep-research quick|standard|max when the user names them. Set expected tool budget.
2. Plan sub-questions — List facets and claims to verify; note which are high-stakes (citation audit mandatory). Prefer internal → official → web (AGENTS.md data source order) when gathering evidence.
3. Parallel pass — Batch web_search / web_fetch per independent facet; optional subagents with tight scopes and structured handoff.
4. Merge — One synthesis pass; resolve contradictions; prefer primary sources.
5. Gap closure — List unresolved material gaps; targeted follow-up searches or explicit “blocked” notes.
6. Citation audit — For mandatory cases: every key finding → source row or unsupported / inferential (AGENTS.md).
7. Deliver — Default report shape, contract JSON, or consumer-specific packet from AGENTS.md; include Limitations and Research trace when depth is standard/deep or requested (APPEND_SYSTEM.md).
8. Log — Append a row to workspace-researcher/MEMORY.md → Research History (topic, task class, tool bucket, major gaps, notable sources).

Scout scripts → pipeline step

Run from the installed skill directory, or adjust paths to absolute locations. Policy defaults to ./scripts/policy.json next to the bundled scripts.

Step	Script	When
After depth + topic fixed	./scripts/scout_query_plan.py	Emit ordered queries (Q001…) and plan_hash for the research trace
After URL collection	./scripts/scout_normalize_sources.py	Dedupe and sort sources before the final table
Long / multi-session runs	./scripts/scout_evidence_bundle.py	Freeze fetch records (JSONL → evidence_bundle.json + content_sha256)
Before high-stakes delivery	./scripts/scout_citation_audit.py	Gate: every key_findings[] row has source_ids or unsupported / inferential

Details and exit codes: ./scripts/README.md.

Handoff schema (optional, for subagents)

## Scope
[One sentence]

## Findings
- [Bullet + URL]

## Gaps
- [What could not be verified]

## Sources touched
- [Title](URL) — quality flag

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Scout skill — Orchestrated research pipeline · 2026-04-10