How do I install the Research Orchestration skill?

Run npx skillmds@latest add firstp1ck/research-orchestration in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Research Orchestration safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Research Orchestration?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Research Orchestration free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Research Orchestration?

Firstp1ck (@firstp1ck) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Research Orchestration by firstp1ck

Name: Research Orchestration
Author: Firstp1ck

Research Orchestration

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.

Firstp1ck Updated Sep 22, 2026

File contents

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

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.
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.
Parallel pass — Batch web_search / web_fetch per independent facet; optional subagents with tight scopes and structured handoff.
Merge — One synthesis pass; resolve contradictions; prefer primary sources.
Gap closure — List unresolved material gaps; targeted follow-up searches or explicit “blocked” notes.
Citation audit — For mandatory cases: every key finding → source row or unsupported / inferential (AGENTS.md).
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).
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

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

---name: research-orchestrationdescription: 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 orchestrationSingle 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.## Pipeline1. **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 stepRun 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)```markdown## Scope[One sentence]## Findings- [Bullet + URL]## Gaps- [What could not be verified]## Sources touched- [Title](URL) — quality flag```---_Scout skill — Orchestrated research pipeline · 2026-04-10_

Frequently asked questions