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name: research-planner description: Create detailed research plans by decomposing structured prompts into subtopics, search strategies, and agent deployment configurations. Extracted from Phase 2 of research-executor for standalone planning capabilities.

Research Planner

Overview

Takes a structured research prompt (from question-refiner) and creates a comprehensive execution plan with subtopic decomposition, search strategies, and multi-agent deployment configuration.

When to Use

• User has structured prompt and wants to review plan before execution
• Need to estimate resources (agents, time, cost) for research
• Want to modify/approve plan before committing to execution
• Planning complex research requiring strategic review

Architecture Position

Copyquestion-refiner (structured prompt)
         ↓
   research-planner (this skill)
         ↓
   research-executor (validates & executes)

Input Requirements

Required: Structured prompt with TASK, CONTEXT, SPECIFIC_QUESTIONS, KEYWORDS, CONSTRAINTS, OUTPUT_FORMAT

Optional: Complexity level, budget constraints, preferred agent types

Output Structure

Copy# Research Plan: [Topic]

## 1. Executive Summary
- Topic, Research Type, Complexity
- Estimated Duration: [15-90 min]
- Estimated Cost: [$X]

## 2. Subtopic Decomposition
[3-7 subtopics with priority]

## 3. Search Strategies
[3-5 queries per subtopic]

## 4. Data Sources
| Source Type | Priority | Rationale |

## 5. Agent Deployment
- Total Agents: [3-8]
- Model Mix: [sonnet + haiku]
- Assignments per agent

## 6. Resource Estimation
| Resource | Estimate |
|----------|----------|
| Time | X min |
| Tokens | X |
| Agents | X |

## 7. Quality Gates
- Phase 3: ≥80% agent success
- Phase 5: ≥30 citations
- Final: Quality ≥8.0

## 8. Approval Options
✅ Approve | 🔧 Modify | 🔄 Alternative | ❌ Cancel

Agent Deployment Matrix

Resource Estimation

CopyTime (min) = 15 + (subtopics × 5) + (agents × 3)
Tokens = agents × 15,000 + 10,000 (overhead)

Plan Modification Support

Users can request:

• Add/remove subtopics
• Adjust agent count or model mix
• Change time/cost budget
• Modify search strategies

Integration

Upstream: question-refiner (structured prompt) Downstream: research-executor (execution plan) Parallel: ontology-scout (domain reconnaissance)

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See also: Skill Base Template

Examples

See examples.md for planning scenarios.

Detailed Instructions

See instructions.md for implementation guide.