architect
Given a PRD, produces an implementation architecture: file tree, component breakdown, data model, and a phased build plan with…
Focused research investigations. Converts questions into structured findings with confidence levels and source citations. Single agent by default; with --parallel (or when the question decomposes into 3+ independent angles) it spawns scout agents whose findings are compressed
Claude Code
$ npx -y skills add SethGammon/Citadel --skill research --agent claude-code
Codex
$ npx skills add SethGammon/Citadel --skill research -a codex -y
Cursor
$ npx skills add SethGammon/Citadel --skill research -a cursor -y
Gemini CLI
$ npx skills add SethGammon/Citadel --skill research -a gemini-cli -y
GitHub Copilot
$ npx skills add SethGammon/Citadel --skill research -a github-copilot -y
OpenCode
$ npx skills add SethGammon/Citadel --skill research -a opencode -y
Windsurf
$ npx skills add SethGammon/Citadel --skill research -a windsurf -y
name: research license: MIT description: >- Focused research investigations. Converts questions into structured findings with confidence levels and source citations. Single agent by default; with --parallel (or when the question decomposes into 3+ independent angles) it spawns scout agents whose findings are compressed into a unified brief. Does not make decisions; produces information that informs the next step. user-invocable: true auto-trigger: false trigger_keywords: - research - investigate - look into - find out - research fleet - parallel research - multi-angle research - compare options last-updated: 2026-07-21
**Don't use when:** you need to act on findings immediately (use /marshal which calls /research internally).
**Single (default):** one agent, 2-4 queries, 3-6 sources. Steps 1-5 below.
**Parallel (`/research --parallel`):** scout agents investigate independent angles of the same question using Fleet wave mechanics. See Parallel Mode below. Without the flag, prefer parallel mode (and say so in the plan) when the question naturally decomposes into 3+ independent angles: evaluating multiple competing technologies or approaches, distinct sub-questions that don't depend on each other, or time-sensitive research where parallel execution matters.
If the question is narrow and focused, stay single-agent. Don't parallelize what a single agent can answer in 5 minutes.
Convert the research question into 2-4 specific search queries:
State the question clearly in one sentence before searching.
Execute searches and read actual content (not just snippets):
The WebFetch Restrictions under Parallel Mode apply in single mode too: never WebFetch rendered GitHub pages.
For each finding, record:
Write findings to `.planning/research/{topic-slug}.md`:
# Research: {Topic}
> Question: {The original question}
> Date: {ISO date}
> Confidence: {overall: high/medium/low}
## Findings
### 1. {Finding title}
**What:** {description}
**Source:** {URL}
**Confidence:** {high/medium/low}
**Action:** {recommendation or "informational"}
### 2. {Finding title}
...
## Summary
{2-3 sentences: what was learned, what the recommendation is}
## Open Questions
{Anything that couldn't be resolved — needs human judgment or deeper investigation}
````
### Step 5: RETURN
Return the summary and recommendation to the caller (user, Marshal, or Archon).
The research document persists for future reference.
## Parallel Mode (--parallel)
The former /research-fleet behavior now lives in this parallel mode. Spawns
multiple scout agents, each investigating a different angle of the same
question. Findings are compressed between waves. Produces a unified research
brief from multiple independent perspectives.
**Inputs:** the question, plus optional **angles** (specific sub-questions to
investigate). If not provided, decompose the question into 3-5 angles
automatically.
### Step P1: DECOMPOSE
Break the research question into 3-5 independent angles:
Example: "Should we migrate from Express to Fastify?"
- Scout 1: Performance benchmarks (Express vs Fastify vs Hono, latest data)
- Scout 2: Migration effort (breaking changes, middleware compatibility, ecosystem)
- Scout 3: Community health (GitHub stars trend, npm downloads, maintainer activity)
- Scout 4: Production war stories (who migrated, what broke, was it worth it)
Each angle must be:
- Independent (scout doesn't need another scout's findings to do its work)
- Specific (one clear question per scout)
- Answerable (3-6 sources should be sufficient)
#### Step P1b: INITIALIZE GRAPH (Explicit Opt-In)
With explicit `--operation-graph`, assign 3-5 opaque angle IDs and initialize a graph plus bound operation:
`node .citadel/scripts/operation-graph-runner.js research-init --project-root . --graph .planning/research/fleet-{slug}/operation-graph.json --operation .planning/research/fleet-{slug}/operation-spec.json --journal .planning/research/fleet-{slug}/graph-journal --run-id research-{slug} --angles {id1,id2,id3}`
For each P2-P5 node, call `node .citadel/scripts/operation-graph-effects.js start` with the graph journal, `--effects .../effect-journal`, node ID, and payload digest before work; call `node .citadel/scripts/operation-graph-effects.js complete` with its evidence digest after verification. Keep prompts and findings outside graph state.
On resume run `node .citadel/scripts/operatioAn open-source operating layer for Claude Code and OpenAI Codex. Citadel routes requests, preserves repository state between sessions, coordinates parallel work, applies repository safeguards, and records evidence and handoffs around the coding agent you
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