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Vc Scout

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withkynam
vc-scout

Fast codebase scouting using shell search and optional parallel research agents. Use for file discovery, task context gathering, and quick scoped searches across directories.

Overview

Publisherwithkynam
Repositoryvibecode-pro-max-kit
Skill namevc-scout
Stars
1.1K
Forks
234
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by withkynam on GitHub. Read the source before you install it.

Installation

Install the Vc Scout AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/withkynam/vibecode-pro-max-kit/tree/main/.claude/skills/vc-scout
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/withkynam/vibecode-pro-max-kit.git /tmp/vibecode-pro-max-kit
mkdir -p .claude/skills
cp -r /tmp/vibecode-pro-max-kit/.claude/skills/vc-scout .claude/skills/vc-scout
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vc Scout in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Vc Scout on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Vc Scout is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Scout

Output style: Follow process/development-protocols/communication-standards.md — answer-first, plain language, no unexplained jargon, TL;DR on long responses.

Fast, token-efficient codebase scouting using parallel agents to find files needed for tasks.

Arguments

  • Default: Scout using local shell search plus optional parallel research-agent delegation (./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. Use local shell search first, then optionally spawn parallel research-agent workers with divided directories when the search space is large
  4. Collect results into concise report

Configuration

Read from .claude/.vc.json (falls back to legacy .claude/.ck.json if present):

  • 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

  • Parallel task registration and external orchestration patterns are optional, not required for normal scouting in this repo
  • See references/task-management-scouting.md only when you are intentionally coordinating a larger parallel scout workflow

4. Spawn Parallel Agents

Load appropriate reference based on decision tree:

  • Internal (Default): references/internal-scouting.md (shell search plus optional research-agent parallelism)
  • External: references/external-scouting.md (Gemini/OpenCode)

Notes:

  • TaskUpdate each task to in_progress before spawning its agent (skip if Task tools unavailable)
  • 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 (skip if Task tools unavailable)
  • 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 shell search and optional parallel research-agent work
  • references/external-scouting.md - Using Gemini/OpenCode CLI
  • references/task-management-scouting.md - Optional task-registration patterns for larger scout coordination

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Vc Scout AI skill do?

Fast codebase scouting using shell search and optional parallel research agents. Use for file discovery, task context gathering, and quick scoped searches across directories.

Why use Vc Scout on TypingMind?

Because you install it once and use it with any model. Vc Scout is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Vc Scout in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/withkynam/vibecode-pro-max-kit/tree/main/.claude/skills/vc-scout. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Vc Scout?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Vc Scout?

As many as you like. As long as a model supports skills, you can use Vc Scout with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Vc Scout AI skill free?

Yes. It is published on GitHub by withkynam under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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