research:prior-art git:20260724.2913803A

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---
name: research:prior-art
description: |
  Research existing solutions when exploring a new problem space. Use when the user mentions "prior art", "existing solutions", "what libraries exist for", or wants to understand the landscape before building.
argument-hint: <topic>
disable-model-invocation: true
---

Research prior art for: $ARGUMENTS

## Process

### Search

Identify relevant sources based on context:
- **GitHub**: Search for repositories matching the problem space
- **Package registries**: npm, PyPI, crates.io, pkg.go.dev—infer from current project or query
- **Web search**: For broader landscape understanding

Run searches in parallel. Infer the ecosystem from:
1. Current project's language/framework (if present)
2. Query terms (e.g., "React hook for X" implies npm)
3. Ask only if genuinely ambiguous

### Investigation

Start with 2-3 most promising projects:
1. Read README and high-level docs to assess relevance
2. Examine code only when relevance is confirmed AND implementation details matter
3. Dispatch parallel `Agent` calls per project, with explicit focus areas

If results don't satisfy the query, expand to more projects.

**Agent dispatch example:**
```
Investigate [project] for prior art on [topic]:
- How does it approach [specific aspect]?
- What tradeoffs does it make?
- What can we learn for our use case?
```

### Synthesis

Gather findings and produce a recommendation:
- Identify common patterns across solutions
- Note meaningful variations in approach
- Infer intent:
  - "build X" → learn patterns, inform implementation
  - "library for X" → find dependencies to use directly

## Output Format

Respond in the conversation with structured markdown, not files:

```markdown
## Prior Art: [Topic]

### Summary
[Common patterns, key variations, recommendation based on query intent]

### Projects

#### [Project Name]
- **Repository**: [link]
- **Relevance**: [why this matters to the query]
- **Approach**: [how it solves the problem]
- **Lessons**: [what to learn from it]

#### [Next Project]
...

### Additional Projects (not deeply investigated)
- [Project]: [one-line description]
- ...
```

## Behavior Guidelines

- **Honest reporting**: Acknowledge when prior art is sparse—don't force results
- **Research only**: Don't offer to integrate dependencies or modify the project
- **Ecosystem inference**: Derive from context, don't require explicit specification
- **Adaptive depth**: Investigate more projects if the initial batch is insufficient