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Acreadiness Generate Instructions

OrganizationPopular
github
acreadiness-generate-instructions

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

Overview

Publishergithub
Repositoryawesome-copilot
Skill nameacreadiness-generate-instructions
Stars
39.1K
Forks
5K
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 github on GitHub. Read the source before you install it.

Installation

Install the Acreadiness Generate Instructions 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/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/acreadiness-generate-instructions .claude/skills/acreadiness-generate-instructions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Acreadiness Generate Instructions 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 Acreadiness Generate Instructions 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 Acreadiness Generate Instructions 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.

/acreadiness-generate-instructions — write AI agent instructions

Use this skill whenever the user wants to create, regenerate, or refresh their custom instructions for AI coding agents (Copilot, Claude, etc.). This is the Generate step in AgentRC's Measure → Generate → Maintain loop and the single highest-leverage action for the AI Tooling pillar.

Output options

VS Code recognises several instruction file types — AgentRC generates the most common ones:

FileScopeWhen to use
.github/copilot-instructions.mdAlways-on, whole workspaceDefault — VS Code Copilot's native instruction file
AGENTS.mdAlways-on, whole workspaceMulti-agent repos (Copilot + Claude + others)
.github/instructions/*.instructions.mdScoped by applyTo globPer-area / per-language rules in monorepos
CLAUDE.mdClaude-specificAdd via --claude-md (nested only)

Strategies

  • flat (default) — single .github/copilot-instructions.md at the chosen path. Simple, easy to review.
  • nested — hub at .github/copilot-instructions.md + per-topic detail files at .github/instructions/<topic>.instructions.md, each with an applyTo glob so VS Code only loads the topic when it's relevant. Better for large or multi-stack repos.

Why .github/instructions/ and not .agents/? AgentRC's default nested layout writes to .agents/, which is the right home for agent-agnostic repos (Copilot + Claude + Cursor reading AGENTS.md). For VS Code Copilot specifically, the native location is .github/instructions/ with applyTo frontmatter — that's what Copilot auto-discovers. This skill rewrites AgentRC's nested output to the VS Code-native location whenever the main output is .github/copilot-instructions.md. If you instead chose --output AGENTS.md, nested keeps AgentRC's default .agents/ layout.

For monorepos, generate area-scoped instructions with --areas, --area <name>, or --areas-only. Areas are defined in agentrc.config.json. Per-area output is written as VS Code .instructions.md files with an applyTo glob (see below).

Topic vs area .instructions.md files

Both end up in .github/instructions/ but they answer different questions:

KindFilename exampleapplyTo exampleWhere it comes from
Topic (nested)testing.instructions.md**/*.{test,spec}.{ts,tsx,js}AgentRC --strategy nested topic split
Area (monorepo)frontend.instructions.mdapps/frontend/**agentrc.config.json areas + --areas

You can have both at once: a nested set of topic files plus per-area files for a monorepo.

Per-area files with applyTo

When the user opts into areas, emit one VS Code-native .instructions.md file per area at .github/instructions/<area>.instructions.md. Each file MUST start with frontmatter declaring the glob the rules apply to:

markdown
---
applyTo: "apps/frontend/**"
---

# Frontend area instructions

…AgentRC-generated content for this area…

Workflow:

  1. Read agentrc.config.json to discover declared areas and their paths / globs. If paths is missing, ask the user for the glob (e.g. src/api/**).
  2. Run agentrc instructions --areas (or --area <name>) to produce the per-area body content.
  3. Wrap each area's content in .github/instructions/<area>.instructions.md with the applyTo frontmatter taken from the area's paths. If the user passed --apply-to <glob> on a single-area call, use that glob verbatim.
  4. Leave the main file alone — the root .github/copilot-instructions.md stays as the always-on instructions; .instructions.md files only kick in for matching paths.

Naming: lowercase, kebab-case area name. Examples: .github/instructions/frontend.instructions.md, .github/instructions/api.instructions.md, .github/instructions/infra.instructions.md.

Steps

  1. Pick the target file. Default to .github/copilot-instructions.md. Switch to AGENTS.md only if the user mentions multi-agent / Claude / Cursor support.
  2. Always ask which strategy to useflat or nested — unless the user already specified one in their message or via --strategy. Present the trade-off briefly:
    • Flat (default) — one .github/copilot-instructions.md. Simple, easy to review in a single PR. Best for small/medium repos with one stack.
    • Nested — hub .github/copilot-instructions.md + per-topic .github/instructions/<topic>.instructions.md files (each with an applyTo glob so VS Code only loads them when relevant). Best for large or multi-stack repos. Add --claude-md to also emit CLAUDE.md. Recommend nested proactively when the repo has > 5 top-level directories, multiple stacks, or already uses a monorepo tool (turbo/nx/pnpm workspaces).
  3. Detect monorepo areas by reading agentrc.config.json. If areas exist, ask the user whether they want per-area .instructions.md files with applyTo in addition to the root file. Default to "yes" when agentrc.config.json declares areas.
  4. Run dry-run first so the user can preview:
    bash
    npx -y github:microsoft/agentrc instructions --output <file> --strategy <flat|nested> [--areas|--area <name>] [--claude-md] --dry-run
  5. Show a short summary of what would change — files that would be created or overwritten, area count + their applyTo globs, model used (default claude-sonnet-4.6).
  6. On confirmation, run the same command without --dry-run (and optionally --force if files already exist).
  7. Post-process layout for Copilot output:
    • If --output ends in copilot-instructions.md and strategy is nested: move/rewrite AgentRC's .agents/<topic>.md files to .github/instructions/<topic>.instructions.md. Add frontmatter to each file with an appropriate applyTo glob (see "Topic applyTo defaults" below). Delete the now-empty .agents/ directory.
    • If --areas was used: also write .github/instructions/<area>.instructions.md for every area, using each area's paths from agentrc.config.json as the applyTo glob (override with --apply-to for single-area calls).
    • If --output AGENTS.md was chosen: keep AgentRC's native .agents/ layout for nested — agent-agnostic readers expect it there. Create the .github/instructions/ directory if missing.

Topic applyTo defaults

When promoting AgentRC's nested topic files to .instructions.md, use these defaults unless the user specifies otherwise:

TopicDefault applyTo
testing**/*.{test,spec}.{ts,tsx,js,jsx,mjs,cjs}
style / code-quality / formatting**/*.{ts,tsx,js,jsx,mjs,cjs,py,go,rs,java,kt,cs}
build / ci**/{package.json,turbo.json,nx.json,.github/workflows/**}
docs**/*.md
security**
anything else / hub-level**
  1. Verify by reading the generated file(s) back and showing the user a 1-paragraph synopsis: stack detected, conventions captured, length, list of .instructions.md files with their globs.
  2. Suggest next steps:
    • Re-run the assess skill to confirm the AI Tooling pillar score improved.
    • If the user already has both copilot-instructions.md and AGENTS.md, recommend consolidating to a single source of truth (AgentRC flags this at maturity Level 2+).

Notes

  • AgentRC reads your actual code — no templates. Output reflects detected languages, frameworks, and conventions.
  • --claude-md (nested strategy only) also emits CLAUDE.md.
  • VS Code applies .instructions.md files automatically when the active file matches applyTo. The root .github/copilot-instructions.md always loads.
  • Never run this skill non-interactively in CI; instructions are part of the repo and should land via PR.

Frequently asked questions

What does the Acreadiness Generate Instructions AI skill do?

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

Why use Acreadiness Generate Instructions on TypingMind?

Because you install it once and use it with any model. Acreadiness Generate Instructions 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 Acreadiness Generate Instructions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/acreadiness-generate-instructions. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Acreadiness Generate Instructions?

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 Acreadiness Generate Instructions?

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

Is the Acreadiness Generate Instructions AI skill free?

Yes. It is published on GitHub by github 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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