home / skills / poemswe / co-researcher / research
This skill coordinates intelligent agents to conduct systematic research, generate plans, execute tasks, and synthesize findings into a final report.
npx playbooks add skill poemswe/co-researcher --skill researchReview the files below or copy the command above to add this skill to your agents.
---
name: research
description: Start a research project with intelligent agent orchestration
metadata:
short-description: Intelligent Research Orchestration
---
# /research - Intelligent Research Orchestration
I'll coordinate specialized agents to conduct systematic research on your topic.
## Research Topic
**Query**: $ARGUMENTS
## 🤖 Orchestration Mode
I'll analyze your query and build an execution plan using specialized agents.
**Agent Registry**:
- `literature-reviewer`: Academic source search, citation chains
- `critical-analyzer`: Fallacy detection, bias identification
- `hypothesis-explorer`: Hypothesis formulation, variable mapping
- `lateral-thinker`: Cross-domain analogies, creative thinking
- `qual-researcher`: Thematic analysis, coding strategies
- `quant-analyst`: Statistical methods, effect sizes
- `peer-reviewer`: Manuscript evaluation
- `ethics-expert`: IRB compliance, privacy risks
- `grant-writer`: Grant proposal development, funding strategy
**Orchestration Process**:
1. **Classify Query**: Determine research type
2. **Select Agents**: Choose optimal agent sequence
3. **Generate Plan**: Build execution DAG
4. **Present Plan**: Show workflow to user
5. **Execute**: Run agents sequentially, save outputs
6. **Synthesize**: Integrate outputs, save final report
I'm analyzing your research topic to determine the optimal workflow...
**Proposed Plan**:
[I will generate this based on your query]
**Proceed?** (yes/no/modify)
---
## File Writing Protocol
**CRITICAL**: After plan approval, you MUST save all research outputs to files.
### Step 1: Create Output Directory
After user approves the plan, immediately:
1. Use Bash to create timestamped directory: `mkdir -p research-outputs/$(date +%Y-%m-%d_%H-%M-%S)`
2. Store the full path in a variable for subsequent file writes
3. Confirm directory creation to user
### Step 2: Write Research Plan
Use Write tool to create `00-research-plan.md` in the output directory:
```markdown
# Research Plan: [Query]
**Created**: [Timestamp]
**Query**: [User's research query]
## Selected Agents
1. [agent-name] - [purpose]
2. [agent-name] - [purpose]
...
## Execution Plan
[Full plan as presented to user]
```
### Step 3: Write Agent Outputs
After EACH agent completes execution:
1. Use Write tool to save output to `{NN}-{agent-name}.md`
- NN = sequential number (01, 02, 03, etc.)
- Example: `01-literature-reviewer.md`, `02-critical-analyzer.md`
2. Format:
```markdown
# {Agent Name} Output
**Agent**: {agent-name}
**Executed**: [Timestamp]
---
[Full agent output - preserve all markdown formatting]
```
### Step 4: Write Final Synthesis
After synthesis completes:
1. Use Write tool to save to `final-synthesis.md`
2. Include complete synthesis with all sections
3. Add metadata header with timestamp and agents used
### Error Handling
- If directory creation fails: warn user and continue with conversation-only output
- If Write fails: log error, notify user, continue execution
- Partial results are acceptable if execution is interrupted
---
**Modes Supported**:
- Default: Interactive
- `--auto`: Automatic execution
- `--plan-only`: Show plan only
- `--manual`: Traditional guided mode
**Templates**: `--template=quick|rigorous|comprehensive`
This skill coordinates specialized agents to plan and run systematic research projects. It builds a tailored execution plan, runs agents in sequence, and synthesizes their outputs into a consolidated report. It supports interactive, automated, and plan-only modes to fit different workflows.
The skill classifies your research query, selects an optimal sequence of domain agents (e.g., literature-reviewer, quant-analyst, ethics-expert), and generates an execution DAG. After you approve the plan, it executes agents stepwise, saves each agent's output as files in a timestamped output directory, and produces a final synthesis integrating findings and metadata.
Can I see the plan before any agents run?
Yes — the skill always presents a proposed execution plan and awaits your approval or modification before execution.
How are outputs saved?
After plan approval the skill creates a timestamped output directory and writes a research plan file, each agent's output sequentially, and a final synthesis file with metadata.
What if file creation fails?
The system will warn you, continue with conversation-only outputs, and log write errors so partial results are still usable.