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Adr Skill

Organization
skillrecordings
adr-skill

Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.

Overview

Publisherskillrecordings
Repositoryadr-skill
Skill nameadr-skill
Stars
89
Forks
4
Bundled files
10
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.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Adr Skill 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.
    https://github.com/skillrecordings/adr-skill/tree/main/.agents/skills/adr-skill
  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/skillrecordings/adr-skill.git /tmp/adr-skill
mkdir -p .claude/skills
cp -r /tmp/adr-skill/.agents/skills/adr-skill .claude/skills/adr-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Adr Skill 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 Skill 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 Skill 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 Skill

Philosophy

ADRs created with this skill are agent-first: they are written so that a coding agent can read one and implement the decision without further clarification. Humans review and approve, but the primary consumer is an agent working from the ADR.

This means:

  • Constraints must be explicit and measurable, not vibes
  • Decisions must be specific enough to act on ("use PostgreSQL 16 with pgvector" not "use a database")
  • Consequences must map to concrete follow-up tasks
  • Non-goals must be stated to prevent scope creep
  • The ADR must be self-contained — no tribal knowledge assumptions

Three-Phase Workflow

Every ADR goes through three phases. Do not skip Phase 1.

Phase 1: Capture Intent (Socratic)

Before writing anything, interview the human to understand the decision space. Ask questions one at a time, building on previous answers. Do not dump a list of questions.

Core questions (ask in roughly this order, skip what's already clear from context):

  1. What are you deciding? — Get a short, specific title. Push for a verb phrase ("Choose X", "Adopt Y", "Replace Z with W").
  2. Why now? — What broke, what's changing, or what will break if you do nothing? This is the trigger.
  3. What constraints exist? — Tech stack, timeline, budget, team size, existing code, compliance. Be concrete.
  4. What does success look like? — Measurable outcomes. Push past "it works" to specifics (latency, throughput, DX, maintenance burden).
  5. What options have you considered? — At least two. For each: what's the core tradeoff? If they only have one option, help them articulate why alternatives were rejected.
  6. What's your current lean? — Capture gut intuition early. Often reveals unstated priorities.
  7. Who needs to know or approve? — Decision-makers, consulted experts, informed stakeholders.
  8. What would you tell a new engineer (or agent) implementing this? — This surfaces the practical context that often gets left out.

Adaptive follow-ups: Based on answers, probe deeper where the decision is fuzzy. Common follow-ups:

  • "What's the worst-case outcome if this decision is wrong?"
  • "What would make you revisit this in 6 months?"
  • "Is there anything you're explicitly choosing NOT to do?"
  • "What prior art or existing patterns in the codebase does this relate to?"

When to stop: You have enough when you can mentally draft every section of the ADR without making things up. If you're guessing at any section, ask another question.

Phase 2: Draft the ADR

  1. Choose the ADR directory.

    • If one exists (adr/, docs/adr/, docs/decisions/, etc.), use it.
    • If none exists, create docs/decisions/ (MADR default) or adr/ (simpler repos).
  2. Choose a filename strategy.

    • If existing ADRs use numeric prefixes (0001-...), continue that.
    • Otherwise use slug-only filenames (choose-database.md).
  3. Choose a template.

    • Use assets/templates/adr-simple.md for straightforward decisions (one clear winner, minimal tradeoffs).
    • Use assets/templates/adr-madr.md when you need to document multiple options with structured pros/cons/drivers.
    • See references/template-variants.md for guidance.
  4. Fill every section from Phase 1 answers. Do not leave placeholder text. Every section should contain real content or be removed (optional sections only).

  5. Generate the file.

    • Preferred: run scripts/new_adr.js (handles directory, naming, and optional index updates).
    • If you can't run scripts, copy a template from assets/templates/ and fill it manually.

Phase 3: Review Against Checklist

After drafting, review the ADR against the agent-readiness checklist in references/review-checklist.md. Present findings to the human and iterate.

Key questions the review answers:

  • Could an agent implement this decision from the ADR alone?
  • Are there ambiguities that would cause an agent to guess or ask for clarification?
  • Are consequences actionable (specific tasks, not vague aspirations)?
  • Is the scope bounded (what's in AND what's out)?

Do not finalize until the ADR passes the checklist or the human explicitly accepts the gaps.

Other Operations

Update an Existing ADR

  1. Identify the intent:

    • Accept / reject: change status, add any final context.
    • Deprecate: status → deprecated, explain replacement path.
    • Supersede: create a new ADR, link both ways (old → new, new → old).
    • Add learnings: append to ## More Information with a date stamp. Do not rewrite history.
  2. Use scripts/set_adr_status.js for status changes (supports both YAML front matter and inline status).

Index

If the repo has an ADR index/log file (often README.md or index.md in the ADR dir), keep it updated.

Preferred: let scripts/new_adr.js --update-index do it. Otherwise:

  • Add a bullet entry for the new ADR.
  • Keep ordering consistent (numeric if numbered; date or alpha if slugs).

Bootstrap

When introducing ADRs to a repo that has none:

bash
node /path/to/adr-skill/scripts/bootstrap_adr.js

This creates the directory, an index file, and the first ADR ("Adopt architecture decision records"). Use --json for machine-readable output. Use --dir to override the directory name.

Categories (Large Projects)

For repos with many ADRs, organize by subdirectory:

docs/decisions/
  backend/
    0001-use-postgres.md
  frontend/
    0001-use-react.md
  infrastructure/
    0001-use-terraform.md

Numbers are local to each category. Choose a categorization scheme early (by layer, by domain, by team) and document it in the index.

Resources

scripts/

  • scripts/new_adr.js — create a new ADR file from a template, using repo conventions.
  • scripts/set_adr_status.js — update an ADR status in-place (YAML front matter or inline). Use --json for machine output.
  • scripts/bootstrap_adr.js — create ADR dir, README.md, and initial "Adopt ADRs" decision.

references/

  • references/review-checklist.md — agent-readiness checklist for Phase 3 review.
  • references/adr-conventions.md — directory, filename, status, and lifecycle conventions.
  • references/template-variants.md — when to use simple vs MADR-style templates.
  • references/examples.md — filled-out short and long ADR examples.

assets/

  • assets/templates/adr-simple.md — lean template for straightforward decisions.
  • assets/templates/adr-madr.md — MADR 4.0 template for decisions with multiple options and structured tradeoffs.
  • assets/templates/adr-readme.md — default ADR index scaffold used by scripts/bootstrap_adr.js.

Script Usage

From the target repo root:

bash
# Simple ADR
node /path/to/adr-skill/scripts/new_adr.js --title "Choose database" --status proposed

# MADR-style with options
node /path/to/adr-skill/scripts/new_adr.js --title "Choose database" --template madr --status proposed

# With index update
node /path/to/adr-skill/scripts/new_adr.js --title "Choose database" --status proposed --update-index

# Bootstrap a new repo
node /path/to/adr-skill/scripts/bootstrap_adr.js --dir docs/decisions

Notes:

  • Scripts auto-detect ADR directory and filename strategy.
  • Use --dir and --strategy to override.
  • Use --json to emit machine-readable output.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Adr Skill AI skill do?

Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.

Why use Adr Skill on TypingMind?

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

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

Which AI models can use Adr Skill?

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 Skill?

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

Is the Adr Skill AI skill free?

It is published on GitHub by skillrecordings. Check the repository for licensing terms. 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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