
deep-research
by bsamiee
My Nix based repo for NixOS/Darwin configuration, dotfiles, and more
SKILL.md
name: deep-research type: simple depth: extended description: >- Orchestrates two-round parallel agent research for comprehensive topic exploration. Use when conducting research, exploring complex topics, gathering multi-faceted information, or synthesizing findings from parallel investigation streams.
[H1][DEEP-RESEARCH]
Dictum: Iterative dispatch with inter-round critique maximizes research coverage.
Conduct comprehensive topic research via parallel agent dispatch.
Workflow:
- §ORIENT — Execute 3 Exa searches via
exa-toolsskill, map landscape, extract facets - §ROUND_1 — Dispatch 6-10 agents for breadth coverage via
parallel-dispatchskill - §CRITIQUE_1 — Filter findings, retain quality, build skeleton with gaps
- §ROUND_2 — Dispatch 6-10 agents to flesh out skeleton
- §CRITIQUE_2 — Synthesize holistically, deduplicate, produce final output
Dependencies:
exa-tools— Web search and code context queriesparallel-dispatch— Agent orchestration mechanics
Input:
Topic: Domain to researchOutputPath: Target file path (passed by invoking command, default:report.md)Constraints: Context, scaffold, style from invoking skill
[CRITICAL]:
- [ALWAYS] Main agent writes to
OutputPathonly—no other files. - [ALWAYS] Sub-agents RETURN structured text—main agent is sole file writer.
- [NEVER] Sub-agents use Write, Edit, Bash, or create any files.
[1][ORIENT]
Dictum: Initial queries map landscape before dispatch.
Main agent executes exactly 3 Exa searches via exa-tools skill; these map topic structure.
Map domain landscape; identify facets for agent assignment. Produce facet list (6-10 independent research areas) for Round 1.
[IMPORTANT]:
- [ALWAYS] Execute 3 Exa searches via
exa-toolsskill before dispatch. - [ALWAYS] Extract facet boundaries from results.
- [NEVER] Dispatch before orient completes.
[2][ROUND_1]
Dictum: Breadth via parallel dispatch—6-10 agents exploring independent facets.
Dispatch 6-10 sub-agents via parallel-dispatch. Assign each agent unique scope from orient facets.
Agent Count: Scale by task complexity (default: 8).
Agent Prompt:
Scope: [Specific facet from orient]
Objective: Research this facet comprehensively
Output: Return structured text (CRITICAL → FINDINGS → SOURCES)
Context: [Topic background, constraints]
Constraint: DO NOT write files—return text only
[CRITICAL]:
- [ALWAYS] Dispatch ALL agents in ONE message block.
- [ALWAYS] Include "DO NOT write files" constraint in every agent prompt.
- [NEVER] Create overlapping scopes.
[3][CRITIQUE_1]
Dictum: Main agent builds skeleton—retains quality, identifies gaps.
Main agent (NOT sub-agent) processes Round 1 outputs.
| [INDEX] | [ACTION] | [CRITERIA] |
|---|---|---|
| [1] | Remove | Lacks focus, duplicates content, missing sources, pre-2024, fails quality |
| [2] | Retain | Addresses topic, includes sources, dates 2024-2025, converges across agents |
Skeleton: Build from retained → [Domain N]: [findings] + Gaps: + Depth-Targets:
[CRITICAL] Skeleton is first corpus—Round 2 fleshes it out.
[4][ROUND_2]
Dictum: Depth via parallel dispatch—same agent count, focused on skeleton gaps.
Dispatch 6-10 sub-agents (same count as Round 1) via parallel-dispatch.
Agent Assignment:
| [INDEX] | [TYPE] | [PURPOSE] | [COUNT] |
|---|---|---|---|
| [1] | Focused | Specific gaps from skeleton | 4-6 |
| [2] | Wide | Broader context for areas | 2-4 |
Agent Prompt:
Scope: [Gap or depth-target from skeleton]
Objective: [Focused: fill gap | Wide: broaden context]
Output: Return structured text (CRITICAL → FINDINGS → SOURCES)
Context: [Skeleton content—build on, don't repeat]
Prior: [Relevant Round 1 findings]
Constraint: DO NOT write files—return text only
[CRITICAL]:
- [ALWAYS] Same agent count as Round 1.
- [ALWAYS] Include skeleton context.
- [ALWAYS] Include "DO NOT write files" constraint in every agent prompt.
[5][CRITIQUE_2]
Dictum: Main agent synthesizes holistically—final corpus for downstream use.
Main agent (NOT sub-agent) compiles final research output and writes to OutputPath.
Integrate: Merge Round 2 → skeleton. Cross-reference rounds. Resolve conflicts (prioritize sourced, current, convergent).
Filter: Remove duplicates, out-of-scope content, superseded items, unresolved conflicts.
Write: Single file to OutputPath with structure:
## [1][FINDINGS]— Synthesized research by domain## [2][CONFIDENCE]— High (convergent) | Medium (single-source) | Low (gaps)## [3][SOURCES]— All sources with attribution
[6][VALIDATION]
Dictum: Gates prevent incomplete synthesis.
[VERIFY]:
- Orient: 3 Exa searches executed via
exa-toolsskill - Round 1: 6-10 agents in ONE message, all returned text (no file writes)
- Critique 1: Skeleton built, gaps identified
- Round 2: Same count, focused on skeleton, all returned text (no file writes)
- Critique 2: Final synthesis, duplicates removed
- Single file written to
OutputPathby main agent only
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
3ヶ月以内に更新がある
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
Reviews coming soon