Parallel Research Workflow

Decompose a research question into sub-questions, dispatch parallel agents, and synthesize findings into a persistent report with file:line citations.

Input

Research question from $ARGUMENTS.

If $ARGUMENTS is empty, ask via AskUserQuestion:

yaml

- question: "What would you like to research?"
  options:
    - "How does X work?"
    - "Where is X implemented?"
    - "What patterns does X use?"
    - "Compare approaches for X"

Step 1: Decompose Question

Break the research question into 2-4 sub-questions. Each sub-question maps to an agent type based on its nature:

Question Type	Agent	Model	Purpose
WHERE is X?	locator	haiku	Find file paths grouped by purpose
HOW does X work?	analyzer	sonnet	Trace data flow, describe patterns
WHY is X designed this way?	analyzer	sonnet	Architectural decisions, trade-offs
WHAT PATTERNS does X follow?	pattern-finder	sonnet	Find similar implementations, variations

Decomposition Rules

•Minimum 2 sub-questions, maximum 4
•Each sub-question must be answerable independently
•Always include at least one WHERE question (locator) to ground the research
•Phrase sub-questions to be specific and scoped

Example Decomposition

Question: "How does authentication work in this project?"

#	Sub-question	Agent
1	Where are the authentication files?	locator
2	How does the login flow process requests?	analyzer
3	What patterns do the auth middleware follow?	pattern-finder

Step 2: Generate Slug

Create a URL-safe slug from the research question:

•Lowercase, hyphens for spaces
•Strip articles (a, an, the)
•Max 50 characters
•Example: "How does authentication work?" becomes how-does-authentication-work

Step 3: Dispatch Parallel Agents

Dispatch agents using the Task tool. Maximum 5 parallel agents.

For each sub-question, spawn a Task with:

•Agent context from the corresponding agent file in this plugin's agents/ directory
•Sub-question as the primary prompt
•Project path for codebase access
•Output format requirements per agent type

Locator Agent Task

Prompt the Task with:

text

You are a locator agent. Find WHERE the following exists in the codebase.

Sub-question: {sub-question}
Project root: {project path}

Search using Glob for file patterns and Grep for content.
Use synonym expansion — search multiple term variations:
  "config" also search "settings", "options", "preferences", "conf"
  "error" also search "exception", "failure", "fault"
  "handler" also search "processor", "listener", "callback"
  "auth" also search "login", "session", "token", "credential"

Output format — group files by purpose:
## Files Found
### Implementation
- path/to/file.py — {brief description}
### Tests
- tests/test_file.py — {brief description}
### Configuration
- config/settings.yaml — {brief description}
### Types/Interfaces
- types/models.py — {brief description}
### Documentation
- docs/feature.md — {brief description}

Analyzer Agent Task

Prompt the Task with:

text

You are an analyzer agent. Understand HOW the following works.

Sub-question: {sub-question}
Project root: {project path}
Known files: {locator output if available, otherwise "discover via search"}

Read relevant files. Trace data flow. Document with file:line references.
Every technical claim MUST include a file:line citation.
If uncertain, mark with triangle (caveat indicator).

Output format:
## Analysis: {sub-question}
### Summary
{2-3 sentence answer}
### Data Flow
1. Entry point: path/file.py:42 — {description}
2. Processing: path/other.py:15 — {description}
3. Output: path/result.py:88 — {description}
### Patterns Observed
- {pattern name}: file.py:10-25 — {how it works}
### Architectural Notes
- {observation with file:line citation}

Pattern-Finder Agent Task

Prompt the Task with:

text

You are a pattern-finder agent. Find existing code patterns to model after.

Sub-question: {sub-question}
Project root: {project path}
Known files: {locator output if available, otherwise "discover via search"}

Find multiple instances of the same pattern. Show each variation with context.
Use synonym expansion for search terms.
Max 20 lines per code snippet.

Output format:
## Patterns: {what was searched}
### Variation 1: {location}
File: path/to/file.py:15-30
{code snippet}
Context: {why this instance is relevant}
### Variation 2: {location}
File: path/to/other.py:42-55
{code snippet}
Context: {how this differs from variation 1}
### Recommendation
{which variation to follow and why}

Step 4: 2-Action Rule

After every 2 search/read operations within any agent, save intermediate findings.

•If docs/plans/{slug}-findings.md exists, append findings there
•Otherwise, keep intermediate state in agent context
•This prevents loss of progress on long research tasks

Step 5: Collect and Reconcile Results

Gather outputs from all completed agents. Check for conflicts:

Conflict Type	Resolution
Different files cited for same function	Verify which is current via git log
Contradictory behavior descriptions	Re-read the disputed file, report both interpretations
Missing coverage	Note in Gaps section

Flag any conflicts explicitly in the report. Do not silently resolve them.

Step 6: Write Research Report

Read the template at ${CLAUDE_PLUGIN_ROOT}/templates/research-report.md.

Write the report to docs/research/{slug}-report.md with this structure:

YAML Frontmatter

yaml

---
question: {original research question}
date: {YYYY-MM-DD}
agents: [locator, analyzer, pattern-finder]
status: complete | partial | inconclusive
---

Status meanings:

Status	Meaning
complete	All sub-questions answered with citations
partial	Some sub-questions unanswered or missing citations
inconclusive	Conflicting findings or insufficient evidence

_OVERVIEW Section

2-3 sentence direct answer to the original question. No hedging. If uncertain, state what IS known and what IS NOT.

Detail Sections

One section per sub-question. Each section must include:

•Section header matching the sub-question
•Findings with file:line citations
•Code snippets where relevant (max 20 lines each)
•Agent attribution (which agent produced this finding)

Cross-References

Link related findings across sections. Example:

text

The auth middleware (see Section 2) uses the token format defined in Section 3.

Gaps Section

What could not be determined and why. Include:

•Unanswered aspects of the original question
•Files that could not be located
•Suggested next steps for further investigation

Step 7: Update Planning Files

If docs/plans/{slug}-findings.md exists:

•Append key findings from the report
•Include file:line references
•Add date stamp for the research

Rules

Rule	Rationale
file:line references mandatory	Every technical claim must be verifiable
Synonym expansion for searches	Single terms miss aliased concepts
Progressive disclosure	Overview first, details on demand
Max 5 parallel agents	Resource and context limits
2-Action Rule	Prevent progress loss on long research
No fabricated paths	If not found, report that clearly

Synonym Expansion Reference

Primary Term	Also Search
config	settings, options, preferences, conf, configuration
error	exception, failure, fault, err
handler	processor, listener, callback, hook
auth	login, session, token, credential, authentication
test	spec, check, verify, assertion
model	schema, entity, record, type
route	endpoint, path, url, api
store	repository, dao, persistence, database, db
validate	check, verify, sanitize, parse
transform	convert, map, serialize, deserialize

Output

Present the completed report path and a brief summary:

text

## Research Complete

Report: docs/research/{slug}-report.md
Status: {status}
Agents: {count} dispatched, {count} successful

### Key Findings
- {finding 1 with file:line}
- {finding 2 with file:line}
- {finding 3 with file:line}

### Gaps
- {gap 1}