research-fanout

Research Fan-out

Turn one fuzzy research goal into parallel, cost-tiered investigation. Interview to scope → get an approved plan tree → fan out subagents → roll up findings as each completes → deliver a report.

Task: $ARGUMENTS

Distinct from deep-research (non-interactive web-search harness): this skill front-loads an interactive scoping interview and an approvable plan tree, tiers models per branch for cost, and streams a per-fork rollup the user can steer mid-flight.

Stage 1 — Orient

• Read $ARGUMENTS. If clear, go to Stage 2.
• If terms are ambiguous, run 1–3 quick web searches to ground yourself before interviewing. Goal: understand the domain well enough to count research forks correctly — not to answer the question yet.

Stage 2 — Interview (max 3 questions)

Narrow the scope. Hard cap: 3 questions, one at a time.

• Multiple-choice preferred; open-ended when needed.
• After every user answer, reply with a 1–2 sentence glanceable restatement of the understood goal (no more).
• Stop early once scope is clear — do not burn questions for their own sake.

Stage 3 — Plan tree (approval gate)

Present a nested bullet tree — the "big picture" of the research path:

• ~3 top-level branches (adaptive 2–5), each phrased as a question the user should be asking (the unknown unknowns), not a statement.
• Sub-bullets decompose each branch into leaf questions. Leaves are the parallel work units.
• Cap total leaves at ~8 for cost. If trimming, say so and name what was cut.

Then: user approves, or refines free-form. Loop — re-present after each refinement. Do not launch until a clear go-ahead ("go", "run it", "approved").

Stage 4 — Tier and launch

Tag each leaf by intuitive complexity, then launch all leaves as background subagents at max parallelism (single message, multiple dispatches). Use general-purpose agents — web-primary, may also read local files if the topic calls for it.

Tier	Leaf looks like	Claude Code model
Cheap	lookup, fact-gathering, mechanical	claude-haiku-4-5
Standard	typical synthesis / comparison	claude-sonnet-5
Deep	ambiguous, high-judgment, cross-cutting	claude-opus-4-8

On non-Claude hosts, map tiers to that host's cheap / mid / flagship models.

Give each subagent a tight brief and a fixed return shape:

## <leaf question>
- Findings: <concise, evidence-backed>
- Sources: <urls / refs>
- Confidence: high | medium | low
- Gaps: <what it couldn't resolve>

Stage 5 — Live rollup

Monitor the running forks. As each fork completes, post its condensed findings to chat immediately (don't wait for all).

• User may interject with course-corrections → adjust, spawn, or kill remaining forks accordingly.
• User may also stay silent and keep watching — keep rolling up.
• If a fork fails or returns null: note it in one line, continue with the rest.

Stage 6 — Synthesize

When all forks are done:

1. Dedup overlapping findings; flag contradictions between forks explicitly.
2. Write the full report to research/<topic-slug>-YYYY-MM-DD.md — branches as sections, findings, sources, open gaps.
3. Show the executive summary in chat (answer to the original goal + key findings + confidence + what remains unknown).

Anti-patterns

• Don't skip the interview and jump to launching subagents.
• Don't launch before the plan tree is explicitly approved.
• Don't give every leaf the same model — tiering is the cost mechanism.
• Don't batch the rollup into one dump at the end; roll up per-fork completion.
• Don't phrase top-level branches as answers — they are the questions to investigate.
• Don't let leaves sprawl past the cap without telling the user what was cut.