shadow-frog-init Skill
Initialize a shadow knowledge base for any codebase. Creates a .shadow/ directory that mirrors the source tree with markdown files for AI-discovered insights. Run this once per repo before using other shadow-frog skills. Refuses to overwrite an existing .shadow/ unless --reset is passed. Published by microsoft in ShadowFrog.
Decision snapshot
Is this a fit?
Deployment, Documentation, Includes SKILL.md, Reusable instructions
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Copy skill directory
2 months ago · MIT license
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What is shadow-frog-init Skill?
Initialize a shadow knowledge base for any codebase. Creates a .shadow/ directory that mirrors the source tree with markdown files for AI-discovered insights. Run this once per repo before using other shadow-frog skills. Refuses to overwrite an existing .shadow/ unless --reset is passed. Published by microsoft in ShadowFrog. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Deployment
- Documentation
- Deployment use cases
- Documentation use cases
Declared skill metadata
- Source file: skills/shadow-frog-init/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use shadow-frog-init Skill
- Use it for deployment.
- Use it for documentation.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/ShadowFrog
- Skill file: skills/shadow-frog-init/SKILL.md
What it does
Initialize a shadow knowledge base for any codebase. Creates a .shadow/ directory that mirrors the source tree with markdown files for AI-discovered insights. Run this once per repo before using other shadow-frog skills. Refuses to overwrite an existing .shadow/ unless --reset is passed.
Skill instructions
ShadowFrog Init Creates .shadow/ directory with symbol-organized shadow files for every source file. Run once per repo. If .shadow/ exists, ask user to reset or skip. Primary: Python Helper Script The companion script shadow-init.py lives in the same directory as this SKILL.md file. To find and run it: bash Project install (Copilot CLI): python3 .github/skills/shadow-frog-init/shadow-init.py [options] Or for Claude Code: python3 .claude/skills/shadow-frog-init/shadow-init.py [options] IMPORTANT: Run from the repo/worktree root directory. The script auto-detects the root via git rev-parse --show-toplevel, which returns the correct root for regular repos AND worktrees. If auto-detection fails (common when python is routed through Docker or the .git file points to an inaccessible path), pass --root explicitly: bash If auto-detect fails, pass the root explicitly: python3 .github/skills/shadow-frog-init/shadow-init.py --root "$(pwd)" In Docker wrapper scenarios (eval harness), git may not w
Verified compatibility and discovery
Frequently asked questions
What is shadow-frog-init?
shadow-frog-init is a open-source AI agent skill with Copy skill directory. Initialize a shadow knowledge base for any codebase. Creates a .shadow/ directory that mirrors the source tree with markdown files for AI-discovered insights.
Who is shadow-frog-init best for?
shadow-frog-init is best for reusing agent instructions, scripts, and references, deployment workflows, documentation workflows.
How do I install shadow-frog-init?
Install or run shadow-frog-init using Copy skill directory. Check shadow-frog-init for the latest setup command.
Is shadow-frog-init actively maintained?
shadow-frog-init may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
