How does the skill track the changes it makes?

Every modification is recorded in two files: ACTION_LOG.md for human review and ACTION_LOG.jsonl for machine processing.

What happens if there is a file conflict during bootstrap?

Potential conflicts are moved to the .agent-docs/compat/ directory to ensure your original files remain untouched and operational.

Can I run this skill multiple times on the same repository?

Yes, the skill is idempotent, meaning you can run it repeatedly to ensure documentation is up to date without creating redundant or duplicate entries.

Will this skill overwrite my existing documentation?

No, the skill is governed by guardrails that strictly prevent deleting or renaming existing content by default.

Non-Destructive Documentation Bootstrap

Name: Non-Destructive Documentation Bootstrap
Author: CheekyCodexConjurer

byCheekyCodexConjurer

学習とドキュメンテーション

Integrates agent documentation templates into existing repositories safely without overwriting or deleting original content.

概要

The Non-Destructive Bootstrap skill provides an idempotent way to install agent-specific documentation and frameworks into any codebase. It follows a strict merge protocol that ensures existing files are never renamed or deleted, instead focusing on adding missing components and updating references using markers. This skill is essential for developers who need to onboard AI-driven documentation tools into mature projects where preserving the integrity of historical configurations and custom logic is paramount.

主な機能

Idempotent template installation and updates
Automated change logging in Markdown and JSONL formats
Conflict isolation in .agent-docs/compat/ folder
In-place reference updates using marker-based injection
0 GitHub stars
Non-destructive merge protocol for existing files

ユースケース

Standardizing repository metadata across multiple quantitative research labs
Updating documentation templates while preserving custom user modifications
Bootstrapping AI agent documentation into a legacy project without data loss

概要

主な機能

Idempotent template installation and updates
Automated change logging in Markdown and JSONL formats
Conflict isolation in .agent-docs/compat/ folder
In-place reference updates using marker-based injection
0 GitHub stars
Non-destructive merge protocol for existing files

ユースケース

Standardizing repository metadata across multiple quantitative research labs
Updating documentation templates while preserving custom user modifications
Bootstrapping AI agent documentation into a legacy project without data loss