plugins/adr-manager/skills/adr-management/SKILL.md
ADR management skill. Auto-invoked for generating architecture decisions, documenting design rationale, and maintaining the decision record log. Uses native read/write tools to scaffold and update ADR markdown files.
npx skillsauth add richfrem/agent-plugins-skills adr-managementInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
This skill requires Python 3.8+ and standard library only. No external packages needed.
To install this skill's dependencies:
pip-compile ./requirements.in
pip install -r ./requirements.txt
See requirements.txt for the dependency lockfile (currently empty — standard library only).
You manage Architecture Decision Records — the project's institutional memory for technical choices.
Document, Decide, and Distribute. Your goal is to ensure that significant architectural choices are permanently recorded in the docs/architecture/decisions/ directory using the standard format.
Canonical path (use this — agents run from the root of the current skill folder):
./scripts/adr_manager.py
./scripts/next_number.py
Always invoke with the root-relative path:
python ./scripts/adr_manager.py <command>
python ./scripts/next_number.py --type adr
Do NOT use ./adr_manager.py (relative to script dir — breaks from project root).
When asked to create an Architecture Decision Record (ADR):
ADRs/ directory at the project root.create subcommand. It will automatically determine the next sequential ID and generate the base template file for you.python ./scripts/adr_manager.py create "Use Python 3.12" --context "..." --decision "..." --consequences "...".md file to stdout.Proposed or Accepted.Superseded and add a note linking to the new ADR.python ./scripts/adr_manager.py list
python ./scripts/adr_manager.py list --limit 10
python ./scripts/adr_manager.py get 42
python ./scripts/adr_manager.py search "ChromaDB"
Use next_number.py to identify the next sequential ID across various artifact domains.
python ./scripts/next_number.py --type adrNNN-short-descriptive-title.md.tools
Ingests repository files into the ChromaDB vector store. Builds or updates the vector index from a manifest or directory scan using ingest.py. Use when new files need to be indexed or the vector store is out of date. <example> user: "Index these new plugin files into the vector database" assistant: "I'll use vector-db-ingest to add them to the vector store." </example> <example> user: "The vector store is missing recent files -- update it" assistant: "I'll use vector-db-ingest to re-index the changes." </example>
data-ai
Removes stale and orphaned chunks from the ChromaDB vector store for files that have been deleted or renamed. Use after files are removed or moved to keep the vector index in sync with the filesystem. <example> user: "Clean up the vector store after I deleted some files" assistant: "I'll use vector-db-cleanup to remove orphaned chunks." </example> <example> user: "The vector database has chunks for files that no longer exist" assistant: "I'll run vector-db-cleanup to prune them." </example>
testing
Audit Vector DB coverage -- compares the live filesystem manifest against the ChromaDB index to identify coverage gaps.
development
3-Phase Knowledge Search strategy for the RLM Factory ecosystem. Auto-invoked when tasks involve finding code, documentation, or architecture context in the repository. Enforces the optimal search order: RLM Summary Scan (O(1)) -> Vector DB Semantic Search -> Grep/Exact Match. Never skip phases.