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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.

shell
$ npx -y skills add bendrucker/claude --skill prior-art --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/prior-art
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

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.

SKILL.md

prior-art.SKILL.md
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:

## 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
Read more
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TypeScript
Language
MIT
License
14h ago
Last commit
1y ago
Created

Repo: bendrucker/claude