When responding to queries about this repository:

1. Suggest relevant commands from the "Essential Commands" section when applicable
2. Highlight Nx's focus on monorepos and its key features like smart task execution, code generation, and project graph analysis
3. Mention the plugin ecosystem and support for various frameworks when relevant
4. Emphasize the importance of running the full validation suite before committing changes

Always strive to provide accurate, helpful responses that align with the best practices and workflows described in this file.

Documentation Contributions

When working on Nx documentation, all documentation content lives in the astro-docs/ folder. This is the new Astro-based documentation site built with Starlight.

Important: Before making any documentation changes, read the astro-docs/README.md file for detailed guidance on:

• Project structure and architecture
• Content types (regular docs, dynamic plugin docs, CLI docs)
• Available Markdoc tags for rich content
• Development workflow and commands
• Sidebar management

Quick Reference

• Documentation content: astro-docs/src/content/docs/
• Use .mdoc (Markdoc) or .mdx format for documentation files
• Run nx serve astro-docs to start the local dev server
• Sidebar structure is defined in astro-docs/sidebar.mts

GitHub Issue Response Mode

When responding to GitHub issues, determine your approach based on how the request is phrased:

Plan-First Mode (Default)

Use this approach when users ask you to:

• "analyze", "investigate", "assess", "review", "examine", or "plan"
• Or when the request is ambiguous

In this mode:

1. Provide a detailed analysis of the issue
2. Create a comprehensive implementation plan
3. Break down the solution into clear steps
4. Then please post the plan as a comment on the issue

Immediate Implementation Mode

Use this approach when users ask you to:

• "fix", "implement", "solve", "build", "create", "update", or "add"
• Or when they explicitly request immediate action

In this mode:

1. Analyze the issue quickly
2. Implement the complete solution immediately
3. Make all necessary code changes. Please make multiple commits so that the changes are easier to review.
4. Run appropriate tests and validation
5. If the tests, are not passing, please fix the issues and continue doing this up to 3 more times until the tests pass
6. Once the tests pass, push a branch and then suggest opening a PR which has a description of the changes made, and that it make sure that it explicitly says "Fixes #ISSUE_NUMBER" to automatically close the issue when the PR is merged.

Avoid making changes to generated files

Files under generated directories are generated based on a different source file and should not be modified directly. Find the underlying source and modify that instead.

Essential Commands

Code Formatting

After code changes are made, please make sure to format the files with prettier via npx prettier -- FILE_NAME

Pre-push Validation

# Full validation suite - run before committing
nx prepush

If the prepush validation suite fails, please fix the issues before proceeding with your work. This ensures that all code adheres to the project's standards and passes all tests. DO NOT make a new commit to fix these issues. Instead, amend the current commit.

Testing Changes in Other Repos

To test a locally built Nx package in another repository (e.g., to verify a fix end-to-end):

pnpm copy-built-package --package nx --repo ../path/to/test-repo

This builds the package and copies it into the target repo's node_modules. It works for all packages including native Rust code.

Testing Changes

After code changes are made, first test the specific project where the changes were made:

nx run-many -t test,build,lint -p PROJECT_NAME

After verifying the individual project, validate that the changes in projects which have been affected:

# Test only affected projects (recommended for development)
nx affected -t build,test,lint

As the last step, run the e2e tests to fully ensure that changes are valid:

# Run affected e2e tests (recommended for development)
nx affected -t e2e-local

Fixing GitHub Issues

When working on a GitHub issue, follow this systematic approach:

1. Get Issue Details

# Get issue details using GitHub CLI (replace ISSUE_NUMBER with actual number)
gh issue view ISSUE_NUMBER

# View multiple issues efficiently in one command
gh issue list --limit 50 --json number,title,state,labels,assignees,updatedAt,body --jq '.[] | select(.number == 123 or .number == 456 or .number == 789)'

# Or filter by specific criteria to get multiple related issues
gh issue list --label "bug" --state "open" --json number,title,body,labels --jq '.[]'
gh issue list --assignee "@me" --json number,title,body,state --jq '.[]'

Tip: Instead of running gh issue view multiple times, use gh issue list with JSON output and filtering to gather information about multiple issues in a single command. This is much more efficient than viewing issues one at a time.

Always provide clickable links: When discussing GitHub issues or PRs, always include the full GitHub URL so the user can easily open them in their browser. For example:

• Issue #12345: https://github.com/nrwl/nx/issues/12345
• PR #67890: https://github.com/nrwl/nx/pull/67890

When cloning reproduction repos, please clone within ./tmp/claude/repro-ISSUE_NUMBER

2. Analyze the Plan

• Look for a plan or implementation details in the issue description
• Check comments for additional context or clarification
• Identify affected projects and components

3. Implement the Solution

• Follow the plan outlined in the issue
• Make focused changes that address the specific problem
• Ensure code follows existing patterns and conventions

4. Run Full Validation

Use the testing workflow from the "Essential Commands" section.

5. Submit Pull Request

• Create a descriptive PR title that references the issue
• Always fill in the PR template - don't leave it empty
• Include "Fixes #ISSUE_NUMBER" in the PR description
• Provide a clear summary of changes made
• Request appropriate reviewers

Pull Request Template

IMPORTANT: When creating a pull request, you MUST fill in the template found in .github/PULL_REQUEST_TEMPLATE.md. Do not leave the template sections empty. The template includes:

Required Sections

1. Current Behavior: Describe the behavior we have today
2. Expected Behavior: Describe the behavior we should expect with the changes in this PR
3. Related Issue(s): Link the issue being fixed so it gets closed when the PR is merged

Template Format

## Current Behavior

<!-- This is the behavior we have today -->

## Expected Behavior

<!-- This is the behavior we should expect with the changes in this PR -->

## Related Issue(s)

<!-- Please link the issue being fixed so it gets closed when this is merged. -->

Fixes #ISSUE_NUMBER

Guidelines

• Ensure your commit message follows the conventional commit format (use pnpm commit)
  • Use fix:, feat:, chore:, etc. as appropriate types.
  • Scope is required for all commits. Possible scopes are listed in scripts/commitizen.js.
• Read the submission guidelines in CONTRIBUTING.md before posting
• For complex changes, you can request a dedicated Nx release by mentioning the Nx team
• Always link the related issue using "Fixes #ISSUE_NUMBER" to automatically close it when merged

General Guidelines for working with Nx

• For navigating/exploring the workspace, invoke the nx-workspace skill first - it has patterns for querying projects, targets, and dependencies
• When running tasks (for example build, lint, test, e2e, etc.), always prefer running the task through nx (i.e. nx run, nx run-many, nx affected) instead of using the underlying tooling directly
• Prefix nx commands with the workspace's package manager (e.g., pnpm nx build, npm exec nx test) - avoids using globally installed CLI
• You have access to the Nx MCP server and its tools, use them to help the user
• For Nx plugin best practices, check node_modules/@nx/<plugin>/PLUGIN.md. Not all plugins have this file - proceed without it if unavailable.
• NEVER guess CLI flags - always check nx_docs or --help first when unsure

Scaffolding & Generators

• For scaffolding tasks (creating apps, libs, project structure, setup), ALWAYS invoke the nx-generate skill FIRST before exploring or calling MCP tools

When to use nx_docs

• USE for: advanced config options, unfamiliar flags, migration guides, plugin configuration, edge cases
• DON'T USE for: basic generator syntax (nx g @nx/react:app), standard commands, things you already know
• The nx-generate skill handles generator discovery internally - don't call nx_docs just to look up generator syntax

Awesome Agent Conventions

A curated field guide to the convention files AI agents read, write, and act on.

22 conventions across 11 categories. From common project instruction files to newer agent-web discovery and trust formats.

Agent tools increasingly rely on plain files in a repository or website root: instructions, memory, rules, tool connections, prompt assets, discovery metadata, and protocol hints. The names are easy to mix up, and the adoption levels vary a lot.

This repo keeps the map practical:

• Know what a file is for. Each entry names the convention, usual filename, primary readers, and spec or source.
• Study real examples. Examples are fetched from public repositories by script, with provenance kept at the top of each file.
• Separate practice from proposal. Maturity labels show what is widely used, what is early, and what is still only proposed.

Contents

• Instruction & context · category page
  • 🟢 AGENTS.md
  • 🟢 CLAUDE.md
  • 🟢 Tool-specific instruction files
  • 🟠 OKF (Open Knowledge Format)
• Memory & state · category page
  • 🟢 MEMORY.md
  • 🟢 Memory Bank
• Spec-driven development · category page
  • 🟢 Spec Kit
  • 🟢 Kiro steering files
• Skills & prompt assets · category page
  • 🟢 SKILL.md
  • 🟢 Prompt asset files
  • 🟢 Claude Code commands
  • 🟢 Copilot prompt & instruction files
• Tooling & connections · category page
  • 🟢 MCP server config
• Rules & ignore files · category page
  • 🟢 Rules files
  • 🟢 AI ignore files
• Design · category page
  • 🟢 DESIGN.md
• Web & discoverability · category page
  • 🟢 llms.txt
  • 🟢 pricing.md
• Agent-web trust · category page
  • 🟠 auth.md
  • 🔵 ai.txt
• Identity & protocols · category page
  • 🟠 Agent Cards (A2A)
• Proposed namespace · category page
  • 🔵 The protocols.md namespace

What counts

This list is intentionally narrow. A file belongs here when it is a convention for agent behavior or agent-readable metadata: instructions, memory, skills, rules, tool config, prompt assets, or web-discovery hints.

Any file type can qualify - .md, .txt, .prompty, .json, dotfiles, or a directory pattern. Human-first project docs such as README.md, CONTRIBUTING.md, SECURITY.md, and CHANGELOG.md stay out unless the file has become an agent convention in its own right.

Maturity tiers

The badge is a claim about adoption, not quality. It keeps a proven convention from being presented the same way as a new idea.

Badge	Tier	Meaning
🟢	Adopted	Used in production by multiple tools, projects, or teams.
🟠	Emerging	Published by a real organization, but still early or limited in adoption.
🔵	Proposed	Publicly described, but without clear adoption beyond the proposal.

Instruction & context

Standalone page: categories/instruction-context.md

	Convention	Files	Read by	Spec
🟢	AGENTS.md	AGENTS.md	Most coding agents - OpenAI Codex, Cursor, Jules, Aider, Gemini CLI, Zed, and others	spec ↗
🟢	CLAUDE.md	CLAUDE.md	Claude Code, and tools that read the Claude memory convention	spec ↗
🟢	Tool-specific instruction files	GEMINI.md AGENT.md QWEN.md WARP.md CONVENTIONS.md copilot-instructions.md	Each file is read by its namesake tool - Gemini CLI, Amp, Qwen Code, Warp, Aider, GitHub Copilot - often alongside or as a bridge to AGENTS.md	spec ↗
🟠	OKF (Open Knowledge Format)	.md	Agents over MCP (okfy, openknowledge, superops okf CLIs); Google's knowledge-catalog ingests bundles	spec ↗

• AGENTS.md - A plain-Markdown "README for agents" - build/test commands, conventions, and gotchas an agent needs before touching the code. The most widely adopted cross-tool instruction file.
• CLAUDE.md - Anthropic's memory file for Claude Code - loaded automatically at session start to carry project commands, style rules, and standing instructions across turns.
• Tool-specific instruction files - Per-tool instruction files that predate or coexist with AGENTS.md. Some tools now default to AGENTS.md while keeping legacy filenames alive, so these variants still matter when auditing real repositories.
• OKF (Open Knowledge Format) - A machine-first organizational knowledge base: a version-controlled folder of typed Markdown files (one concept per file) that any agent reads as ground-truth context. Open-sourced by Google Cloud in 2026 as the content layer to MCP's transport.

Memory & state

Standalone page: categories/memory-state.md

	Convention	Files	Read by	Spec
🟢	MEMORY.md	MEMORY.md	Claude Code's auto-memory - the per-project MEMORY.md index it writes and re-reads each session	spec ↗
🟢	Memory Bank	projectbrief.md productContext.md activeContext.md systemPatterns.md techContext.md progress.md	Cline, Roo Code, and Cursor (via the Memory Bank custom-instructions pattern)	spec ↗

• MEMORY.md - A persistent, agent-maintained index of durable facts - written and re-read across sessions so an agent accumulates project memory instead of relearning each time.
• Memory Bank - Cline's structured memory system - a set of Markdown files an agent reads at the start of every task to reconstruct full project context after its session memory resets. The six files shown are Cline's set; tools like Roo Code use an overlapping but different variant.

Spec-driven development

Standalone page: categories/spec-driven-development.md

	Convention	Files	Read by	Spec
🟢	Spec Kit	constitution.md spec.md plan.md tasks.md	GitHub Spec Kit's slash-command agents (Copilot, Claude, Gemini, Cursor, and more)	spec ↗
🟢	Kiro steering files	product.md structure.md tech.md	AWS Kiro (steering files are largely Kiro-specific)	spec ↗

• Spec Kit - GitHub's spec-driven workflow - a constitution plus per-feature spec → plan → tasks files that drive an agent through structured, reviewable implementation.
• Kiro steering files - Kiro's always-on steering docs - product, structure, and tech files that give the agent persistent project context outside of any single spec.

Skills & prompt assets

Standalone page: categories/skills-prompt-assets.md

	Convention	Files	Read by	Spec
🟢	SKILL.md	SKILL.md	Claude Agent Skills, Claude Code, Amp, Agent Skills-compatible tools	spec ↗
🟢	Prompt asset files	.prompty .prompt system_prompt.txt	Prompty tooling, Azure AI / Semantic Kernel, and apps that load externalized prompts	spec ↗
🟢	Claude Code commands	.md	Claude Code - project .claude/commands/ and user ~/.claude/commands/	spec ↗
🟢	Copilot prompt & instruction files	.prompt.md .instructions.md	GitHub Copilot in VS Code / Copilot CLI	spec ↗

• SKILL.md - A self-contained, model-invoked capability file that tells an agent when to load a reusable procedure and how to execute it.
• Prompt asset files - Externalized prompt files - Prompty's YAML-front-mattered .prompty, plain .prompt templates, and system_prompt.txt - that pull the prompt out of source code so it can be versioned and edited on its own. Only .prompty has a formal spec (prompty.ai); .prompt and system_prompt.txt are ad-hoc externalized-prompt filenames.
• Claude Code commands - A Markdown file Claude Code exposes as a /slash-command - a reusable, version-controlled prompt workflow, with optional frontmatter (allowed-tools, model, argument-hint) and $ARGUMENTS and shell placeholders (@file references are a general Claude Code prompt feature, not command-specific). Now converging with Agent Skills, but still widely committed in its own right.
• Copilot prompt & instruction files - Modular, path-scoped Copilot context: *.instructions.md auto-attach to matching files via an applyTo glob, while *.prompt.md are reusable prompts you invoke by name - the granular cousins of a single .github/copilot-instructions.md.

Tooling & connections

Standalone page: categories/tooling-connections.md

	Convention	Files	Read by	Spec
🟢	MCP server config	.mcp.json	Claude Code, Cursor, VS Code / Copilot, and Claude Desktop - every MCP host reads the same mcpServers schema, though the filename and path differ per tool	spec ↗

• MCP server config - A JSON file that tells an agent which Model Context Protocol servers to launch and how (command, args, env) - making a project's tool and data integrations portable, shareable, and version-controlled across every MCP-capable client.

Rules & ignore files

Standalone page: categories/rules-ignore-files.md

	Convention	Files	Read by	Spec
🟢	Rules files	.cursorrules .mdc .clinerules .clinerules/ (pattern) .windsurfrules	Cursor (.cursorrules / .mdc), Cline (.clinerules/ and legacy .clinerules), Windsurf (.windsurfrules)	spec ↗
🟢	AI ignore files	.aiignore .cursorignore .codeiumignore .aiexclude	JetBrains Junie (.aiignore), Cursor (.cursorignore), Codeium/Windsurf (.codeiumignore)	spec ↗

• Rules files - Per-tool rule files that scope agent behavior - older single-file forms (.cursorrules, .clinerules, .windsurfrules) and newer directory-based, glob-scoped forms (.cursor/rules/.mdc, .clinerules/, .windsurf/rules/.md).
• AI ignore files - gitignore-syntax files that fence an AI agent out of paths - secrets, vendored code, generated output - so they're never sent to the model as context.

Design

Standalone page: categories/design.md

	Convention	Files	Read by	Spec
🟢	DESIGN.md	DESIGN.md	Google Stitch natively; and coding agents (e.g. Claude Code) when pointed at it as design context	spec ↗

• DESIGN.md - A structured, machine-readable design specification - tokens, components, and layout intent - that an agent reads to generate or keep UI consistent with an established system. Open-sourced by Google Labs in 2026 as a cross-tool draft spec.

Web & discoverability

Standalone page: categories/web-discoverability.md

	Convention	Files	Read by	Spec
🟢	llms.txt	llms.txt llms-full.txt (pattern)	Docs sites publish it for LLM tools and crawlers - though no major provider has confirmed reading it	spec ↗
🟢	pricing.md	pricing.md	Agents and LLM browsers fetching a clean, parse-able pricing page	spec ↗

• llms.txt - A proposed-turned-widely-published standard: a root-level Markdown file giving LLMs a curated, link-rich map of a site's docs. Published across hundreds of developer-docs sites - though whether the major LLM providers actually read it remains unproven.
• pricing.md - The Markdown twin of a pricing page - same URL with a .md suffix - so an agent gets structured plans and numbers instead of scraping marketing HTML. A concrete, shipping instance of the page.md pattern.

Agent-web trust

Standalone page: categories/agent-web-trust.md

	Convention	Files	Read by	Spec
🟠	auth.md	auth.md	Agents discovering how to authenticate to a service (early adopters)	spec ↗
🔵	ai.txt	ai.txt	AI training/data-mining crawlers that voluntarily honor AI usage preferences; crawler support is not yet reliable	spec ↗

• auth.md - A Markdown file that tells an agent how to authenticate with a service - discovery of auth endpoints and flows. Shipped by WorkOS as a real, working convention, but adoption beyond it is still early.
• ai.txt - A text file declaring machine-readable consent, licensing, or policy preferences for AI training and data-mining. Spawning popularized the deployed root-file pattern, and a 2026 Internet-Draft now proposes a well-known URI; adoption and crawler obedience are still thin, so it stays 🔵.

Identity & protocols

Standalone page: categories/identity-protocols.md

	Convention	Files	Read by	Spec
🟠	Agent Cards (A2A)	agent-card.json agent.json (pattern)	A2A-compatible agents discovering another agent's capabilities	spec ↗

• Agent Cards (A2A) - The Agent2Agent (A2A) capability card - a JSON document at a well-known path advertising an agent's skills, endpoints, and auth so other agents can discover and call it. Now a Linux Foundation project at v1.0; adoption is growing but early.

Proposed namespace

Standalone page: categories/proposed-namespace.md

	Convention	Files	Read by	Spec
🔵	The protocols.md namespace	proof.md	- (no demonstrated readers; aspirational)	spec ↗

• The protocols.md namespace - A single maintainer's pre-registered namespace of ~74 aspirational .md "protocols" (proof.md, signature.md, reputation.md, …) staked as Schelling points for a future agent web. Published concept, no demonstrated adoption - see the page for the audited, honest caveats.

Maintaining examples

Example files are fetched, not invented. The extractor pulls them from public sources, stores them under conventions/<slug>/examples/<source>/<filename>, and adds a line-1 provenance comment. The examples remain under their upstream owners' licenses and terms; see THIRD_PARTY_EXAMPLES.md before reusing them.

To refresh everything:

pip install -r scripts/requirements.txt
python scripts/extract.py          # fetch real files + rebuild each convention's README
python scripts/build_readme.py     # rebuild this README from scripts/targets.json

Re-running is idempotent. A missing target prints a miss and is skipped. Examples are representative samples: any file over 256 KB (for example, a multi-MB llms-full.txt) is truncated with a marker pointing back to the full source. scripts/targets.json remains the source of truth for conventions that have not been migrated yet; the skill-md pilot uses local convention metadata instead. Edit the relevant source and re-run both scripts.

Shortcut targets are available in the Makefile:

make verify          # schema + generated files + example provenance + links
make extract         # refetch public examples and rebuild generated docs
make license-report  # summarize upstream licenses for vendored examples

CI keeps the generated files and links honest. The verify workflow checks that generated docs match catalog metadata and migrated local metadata, and that every spec, example, and instance URL still resolves on each pull request and weekly. Run the same link check locally with python scripts/check_links.py.

Contributing

Read CONTRIBUTING.md. In short: an entry must pass the filter above and carry evidence for its maturity tier. Add sources to scripts/targets.json for non-migrated conventions, run the scripts, and open a PR. The skill-md pilot uses local convention metadata instead. Do not hand-write example files.

Before proposing adjacent standards, check WATCHLIST.md. Project direction lives in ROADMAP.md.

License

The curation, scripts, and original prose in this repository are MIT. Vendored example files remain under their upstream owners' licenses and terms; see THIRD_PARTY_EXAMPLES.md.