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Adr Index

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ruvnet
adr-index

Build or rebuild the ADR index + dependency graph by running scripts/import.mjs (handles v3-style and plugin-style ADR formats; one Bash call vs hundreds of MCP round-trips)

Overview

Publisherruvnet
Repositoryruflo
Skill nameadr-index
Stars
72.7K
Forks
8.6K
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Adr Index 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.
  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/ruvnet/ruflo.git /tmp/ruflo
mkdir -p .claude/skills
cp -r /tmp/ruflo/plugins/ruflo-adr/skills/adr-index .claude/skills/adr-index
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Adr Index 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 Adr Index 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 Adr Index 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.

ADR Index

Persists every ADR under */docs/adr/ or */docs/adrs/ to the adr-patterns namespace and every relationship (supersedes / amends / related / depends-on) to adr-edges. Handles both ADR formats found in the Ruflo monorepo:

  • v3-style: # ADR-097: Title heading + **Status**: Proposed line
  • plugin-style: YAML frontmatter (id: ADR-NNNN, status: Proposed)

Implementation is in scripts/import.mjs (one Bash call) rather than dozens of per-ADR MCP tool calls — same effective behavior, materially faster, dual-format-aware, and false-positive-resistant for issue numbers.

When to use

  • After importing ADRs from another project
  • When the AgentDB graph is out of sync with the on-disk ADR files
  • Bootstrapping ADR tracking on an existing codebase

Steps

  1. Run the importer:

    bash
    node plugins/ruflo-adr/scripts/import.mjs

    Optional env:

    • IMPORT_FORMAT=json — emit JSON instead of markdown
    • IMPORT_DRY_RUN=1 — parse + summarize, skip persistence
    • ADR_ROOT=/path — scan a different root (default: cwd)
  2. Inspect the summary — total ADRs, stored count, by-status breakdown, edge counts, dangling refs, status mismatches.

  3. Verify graph integrity (optional but recommended) via the sibling adr-verify skill, which runs scripts/verify.mjs and exits 1 on cycles.

  4. Search semantically via mcp__plugin_ruflo-core_ruflo__memory_search against the populated namespace:

    memory_search --query "federation budget" --namespace adr-patterns

Storage shape

adr-patterns namespace, key <ADR-id>::<basename>, value (text):

<title> — <first paragraph of Context>

file: <relative path>
status: <Proposed|Accepted|Superseded|...>
date: <ISO date>
tags: <comma-separated>

adr-edges namespace, deterministic key <relation>:<FROM>-><TO>, value:

json
{ "from": "ADR-097", "to": "ADR-086", "relation": "related", "capturedAt": "<ISO>" }

Both ADR records and relationship edges are stored with explicit upsert semantics. Re-running adr-index refreshes changed metadata in place and does not create duplicate copies of an unchanged semantic edge.

False-positive guard

#1697 / commit abc123 / PR 1234 references inside ADR bodies are stripped before regex extraction so they don't get misread as ADR-1697 etc. See extractAdrRefs() in scripts/import.mjs.

What this skill cannot do

adr-index only ever adds/upserts. If an ADR file was deleted (or a relation line removed from a surviving file), the row it wrote stays forever — adr-verify won't catch it either, since an orphan has no dangling ref and forms no cycle. Use the sibling adr-reindex skill to reconcile a deletion (issue #2666).

Cross-references

  • adr-create — produces the ADR files this skill consumes
  • adr-review — runs over adr-patterns for compliance checks
  • adr-verify (sibling skill) — runs scripts/verify.mjs for graph-integrity gating
  • adr-reindex (sibling skill) — drop-and-rebuild reconcile for a deleted ADR file (this skill can only add, never remove)

Frequently asked questions

What does the Adr Index AI skill do?

Build or rebuild the ADR index + dependency graph by running scripts/import.mjs (handles v3-style and plugin-style ADR formats; one Bash call vs hundreds of MCP round-trips)

Why use Adr Index on TypingMind?

Because you install it once and use it with any model. Adr Index 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 Adr Index in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ruvnet/ruflo/tree/main/plugins/ruflo-adr/skills/adr-index. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Adr Index?

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 Adr Index?

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

Is the Adr Index AI skill free?

Yes. It is published on GitHub by ruvnet 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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