Deep Research

v0.1.0

Automated deep research that performs comprehensive multi-source investigation and produces detailed reports with citations. Use when user requests research,...

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for bird-frank/deep-research-plan.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Deep Research" (bird-frank/deep-research-plan) from ClawHub.
Skill page: https://clawhub.ai/bird-frank/deep-research-plan
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install deep-research-plan

ClawHub CLI

Package manager switcher

npx clawhub@latest install deep-research-plan
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Purpose & Capability
The name/description (deep research, plan + execute) match the SKILL.md steps. The skill requests no binaries, env vars, or installs that would be unrelated to research.
Instruction Scope
Phase 1 is collaborative and must wait for explicit user confirmation (good). Phase 2 instructs the coordinator to spawn a sub-agent (session_spawn) and let it 'independently decide how to search' and 'dynamically add searches' — this is coherent for autonomous research but grants the spawned agent broad discretion to access web sources and create/collect data. The SKILL.md also directs saving plans to plans/research-plan-{timestamp}.json and references a tool name 'deep-research-executor' that is not included here (availability is unknown).
Install Mechanism
Instruction-only skill with no install spec and no code files. Lowest install risk. It will write research-plan JSON files to a local plans/ path during normal operation.
Credentials
No environment variables, credentials, or config paths are required or requested; that is proportionate to an instruction-only research coordinator.
Persistence & Privilege
always:false and user-invocable (normal). However the skill instructs creation of sub-agents via session_spawn which increases the operational blast radius depending on the platform's sub-agent privileges. The skill itself does not request persistent system-wide privileges.
Assessment
This skill appears coherent and doesn't ask for credentials or installs, but before enabling it consider: 1) The skill will spawn a sub-agent that can browse external sources and create files (plans/*.json). Confirm you are comfortable with that agent's web/network/file permissions. 2) The SKILL.md references a tool ('deep-research-executor') and the session_spawn capability — verify those tools exist and what privileges they have on your platform. 3) Keep an eye on the created plans/ files and on outbound queries the sub-agent performs (to avoid accidental data leakage). 4) If you want tighter control, require the coordinator to present the final list of exact sources or deny session_spawn/autonomous browsing before allowing Phase 2.

Like a lobster shell, security has layers — review code before you run it.

latestvk974zfeb1pe3ne9dr3d3tjcbhn836gyw
270downloads
0stars
1versions
Updated 1mo ago
v0.1.0
MIT-0

Deep Research

Two-phase research workflow: planning then execution.

Overview

This skill provides a structured approach to deep research:

Phase 1: Planning (High Freedom)

  • Discuss with user to clarify and refine research questions.
  • Define what to investigate and what the report should cover.
  • Set expectations for research depth and output.
  • Create research plan document.

Phase 2: Execution (Low Freedom)

  • Sub-agent reads the research plan
  • Independently decides how to search for each sub-question
  • Can dynamically add searches based on findings
  • Analyzes content and generates report with citations

Phase 1: Generate Research Plan

The coordinator (main session) performs:

  1. Understand the research topic — Listen to user's request and understand what they want to investigate
  2. Collaborate with user — Discuss and clarify research questions together. Present 3-5 potential sub-questions or research angles for user to review
  3. Define scope together — Discuss what to include/exclude, confirm boundaries of the research
  4. Confirm report expectations — Ask user what sections they want, what depth, any specific focus areas
  5. Get user confirmation — Present the draft plan to user and wait for approval before proceeding
  6. Output: Research plan document — Only after user confirms, save to plans/research-plan-{timestamp}.json

Key principle: The plan is a collaboration between coordinator and user. Never proceed to Phase 2 without explicit user confirmation of the research plan.

Research plan format (JSON):

{
  "topic": "Original research topic",
  "research_questions": [
    "What are the latest breakthroughs in this field?",
    "Who are the leading organizations or researchers?",
    "What are the current limitations or challenges?",
    "What are the practical applications?"
  ],
  "scope": {
    "include": ["recent developments", "key players", "technical details"],
    "exclude": ["historical background before 2020", "unrelated applications"]
  },
  "report_requirements": {
    "sections": ["executive_summary", "findings", "conclusion", "references"],
    "depth": "comprehensive",
    "min_sources": 8,
    "focus_areas": ["technical analysis", "market landscape"]
  }
}

Research Plan Schema

Required fields:

  • topic: Original research topic
  • research_questions: Array of questions to investigate
  • report_requirements: Object specifying output expectations

Optional fields:

  • scope: Define boundaries of research (include/exclude)
  • min_sources: Minimum sources to analyze (default: 8)
  • max_sources: Maximum sources to analyze (default: 20)
  • notes: Additional context or special instructions

Save plan to: plans/research-plan-{timestamp}.json

⚠️ WAIT FOR USER CONFIRMATION — Do not proceed to Phase 2 until user explicitly approves the research plan.

Key principle: The plan defines WHAT to research and WHAT the output should contain. It does NOT specify HOW to search (keywords, sources, rounds) - that is up to the research agent to determine dynamically.

Phase 2: Execute Research Plan

Launch sub agent with the research plan. Launch sub agent with session_spawn tool. Instruct subagent to use deep-research-executor to execute the plan EXPLICITLY.

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