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.
What this skill does
# /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:
| File | Scope | When to use |
|---|---|---|
| `.github/copilot-instructions.md` | Always-on, whole workspace | **Default** — VS Code Copilot's native instruction file |
| `AGENTS.md` | Always-on, whole workspace | Multi-agent repos (Copilot + Claude + others) |
| `.github/instructions/*.instructions.md` | Scoped by `applyTo` glob | Per-area / per-language rules in monorepos |
| `CLAUDE.md` | Claude-specific | Add 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:
| Kind | Filename example | `applyTo` example | Where it comes from |
|---|---|---|---|
| **Topic** (nested) | `testing.instructions.md` | `**/*.{test,spec}.{ts,tsx,js}` | AgentRC `--strategy nested` topic split |
| **Area** (monorepo) | `frontend.instructions.md` | `apps/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 use** — `flat` 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:
| Topic | Default `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 | `**` |
8. **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.
9. **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.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.