Skill: bird-frank/deep-research-plan (version 0.1.0)

--- name: deep-research description: "Automated deep research that performs comprehensive multi-source investigation and produces detailed reports with citations. Use when user requests research, investigation, or in-depth analysis of any topic. Capabilities: generate structured research plans, and start sub agent to execute the plan. " --- # 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): ```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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)