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shadow-frog-dream Skill

AI Agent SkillPythonOpen source

Run autonomous experimentation while the user is AFK. Uses 6 investigation categories (investigation, bug hunting, feature design, refactoring, optimization, security audit) to systematically discover non-obvious behaviors. Every task is an experiment — implement in worktrees, commit to persistent dream branches, and p Published by microsoft in ShadowFrog.

What is shadow-frog-dream Skill?

Run autonomous experimentation while the user is AFK. Uses 6 investigation categories (investigation, bug hunting, feature design, refactoring, optimization, security audit) to systematically discover non-obvious behaviors. Every task is an experiment — implement in worktrees, commit to persistent dream branches, and p 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.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
28/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Security review
  • Design and media
  • Security review use cases
  • Design and media use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use shadow-frog-dream Skill

  • Use it for security review.
  • Use it for design and media.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/ShadowFrog
  • Skill file: skills/shadow-frog-dream/SKILL.md

What it does

Run autonomous experimentation while the user is AFK. Uses 6 investigation categories (investigation, bug hunting, feature design, refactoring, optimization, security audit) to systematically discover non-obvious behaviors. Every task is an experiment — implement in worktrees, commit to persistent dream branches, and p

Skill instructions

ShadowFrog Dream Autonomous experimentation while the user is away. Every task is an experiment — implement real code in a worktree, run it, persist as a named git branch pushed to the fork. Dream's unique value is implementation experience that compounds across sessions. Critical Invariants These rules are stated ONCE here and enforced by helper scripts. Violating any of them is a completion criteria failure. Prerequisite: .shadow/ must be git-tracked Dream moves .shadow/ content through git — artifacts are committed onto the dream branch, pushed to the remote, then read back by the reconciler via git show origin/<branch .shadow/.... If .shadow/ is gitignored (the "local only" option in shadow-frog-init), git add -A silently skips those files, nothing reaches the remote, and the reconciler finds no manifest — every discovery is lost without warning. dream-setup.sh runs git check-ignore .shadow up front and refuses to start if it's ignored. Use shadow-frog-update instead for local-only

Explore related resources

Frequently asked questions

What is shadow-frog-dream?

shadow-frog-dream is a open-source AI agent skill with Copy skill directory. Run autonomous experimentation while the user is AFK. Uses 6 investigation categories (investigation, bug hunting, feature design, refactoring, optimization, security audit) to systematically discover.

Who is shadow-frog-dream best for?

shadow-frog-dream is best for reusing agent instructions, scripts, and references, security review workflows, design and media workflows.

How do I install shadow-frog-dream?

Install or run shadow-frog-dream using Copy skill directory. Check shadow-frog-dream for the latest setup command.

Is shadow-frog-dream actively maintained?

shadow-frog-dream may need a closer maintenance check before production use.

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Stars
13
Forks
3
Last commit
16 days ago
Repository age
2 months
License
MIT

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