ck:scout
Fast codebase scouting using parallel agents. Use for file discovery, task context gathering, quick searches across directories. Supports internal (Explore) and external (Gemini/OpenCode) agents.
Best use case
ck:scout is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Fast codebase scouting using parallel agents. Use for file discovery, task context gathering, quick searches across directories. Supports internal (Explore) and external (Gemini/OpenCode) agents.
Teams using ck:scout should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scout/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ck:scout Compares
| Feature / Agent | ck:scout | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Fast codebase scouting using parallel agents. Use for file discovery, task context gathering, quick searches across directories. Supports internal (Explore) and external (Gemini/OpenCode) agents.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Scout Fast, token-efficient codebase scouting using parallel agents to find files needed for tasks. ## Arguments - Default: Scout using built-in Explore subagents in parallel (`./references/internal-scouting.md`) - `ext`: Scout using external Gemini/OpenCode CLI tools in parallel (`./references/external-scouting.md`) ## When to Use - Beginning work on feature spanning multiple directories - User mentions needing to "find", "locate", or "search for" files - Starting debugging session requiring file relationships understanding - User asks about project structure or where functionality lives - Before changes that might affect multiple codebase parts ## Quick Start 1. Analyze user prompt to identify search targets 2. Use a wide range of Grep and Glob patterns to find relevant files and estimate scale of the codebase 3. Spawn parallel agents with divided directories 4. Collect results into concise report ## Configuration Read from `.claude/.ck.json`: - `gemini.model` - Gemini model (default: `gemini-3-flash-preview`) ## Workflow ### 1. Analyze Task - Parse user prompt for search targets - Identify key directories, patterns, file types, lines of code - Determine optimal SCALE value of subagents to spawn ### 2. Divide and Conquer - Split codebase into logical segments per agent - Assign each agent specific directories or patterns - Ensure no overlap, maximize coverage ### 3. Register Scout Tasks - **Skip if:** Agent count ≤ 2 (overhead exceeds benefit) - `TaskList` first — check for existing scout tasks in session - If not found, `TaskCreate` per agent with scope metadata - See `references/task-management-scouting.md` for patterns and examples ### 4. Spawn Parallel Agents Load appropriate reference based on decision tree: - **Internal (Default):** `references/internal-scouting.md` (Explore subagents) - **External:** `references/external-scouting.md` (Gemini/OpenCode) **Notes:** - `TaskUpdate` each task to `in_progress` before spawning its agent - Prompt detailed instructions for each subagent with exact directories or files it should read - Remember that each subagent has less than 200K tokens of context window - Amount of subagents to-be-spawned depends on the current system resources available and amount of files to be scanned - Each subagent must return a detailed summary report to a main agent ### 5. Collect Results - Timeout: 3 minutes per agent (skip non-responders) - `TaskUpdate` completed tasks; log timed-out agents in report - Aggregate findings into single report - List unresolved questions at end ## Report Format ```markdown # Scout Report ## Relevant Files - `path/to/file.ts` - Brief description - ... ## Unresolved Questions - Any gaps in findings ``` ## References - `references/internal-scouting.md` - Using Explore subagents - `references/external-scouting.md` - Using Gemini/OpenCode CLI - `references/task-management-scouting.md` - Claude Task patterns for scout coordination
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