exploration-strategy

Exploration Strategy

Use fast, parallel exploration to gather context before planning.

Overview

Effective exploration minimizes wasted effort by quickly identifying relevant code, patterns, and conventions. This skill defines exploration patterns, tool selection, and convergence criteria.

Key Principles

1. Parallel over sequential - Run multiple searches simultaneously when possible
2. Targeted over exhaustive - Start with likely locations, expand if needed
3. Converge quickly - Stop when results stabilize or context is sufficient
4. Summarize for handoff - Produce actionable summaries for downstream agents

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Exploration Patterns

Choose the appropriate pattern based on task characteristics.

Breadth-First Exploration

Use when: Structure is unclear or unfamiliar codebase

Approach:

1. Start with high-level structure (directories, entry points)
2. Identify major components and their relationships
3. Narrow focus based on initial findings
4. Deep dive into relevant areas

Example:

Initial: Glob for package.json, setup.py, main entry points
Then:    List top-level directories
Then:    Read README and key configs
Finally: Focus on relevant subsystems

Depth-First Exploration

Use when: Target is known but details are needed

Approach:

1. Start at known entry point
2. Follow imports and references
3. Map the call chain
4. Document dependencies

Example:

Start:   Read specific file mentioned in task
Then:    Follow imports in that file
Then:    Read imported modules
Finally: Document the dependency tree

Targeted Exploration

Use when: Looking for specific patterns or implementations

Approach:

1. Search for specific terms, patterns, or signatures
2. Filter results by relevance
3. Read most promising matches
4. Expand search if needed

Example:

Search:  Grep for function name or pattern
Filter:  Exclude test files if not relevant
Read:    Top 3-5 most relevant matches
Expand:  Broaden search terms if insufficient