Nx is a tool for managing monorepos, which are repositories containing multiple related projects, across TypeScript and other languages. It helps development teams and AI agents run only affected tasks, cache build results, generate code, and coordinate continuous integration. The catalogue add-ons provide agent skills, commands, agents, instructions, and settings for working with Nx.
Borrowing it
Nothing to install: this file belongs to nrwl/nx. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nrwl/nx/master/.claude/commands/gh-issue-plan.mdgit clone --depth 1 https://github.com/nrwl/nxWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/nrwl/nx/gh-issue-plan)<a href="https://agentmods.dev/commands/nrwl/nx/gh-issue-plan"><img src="https://agentmods.dev/badge/commands/nrwl/nx/gh-issue-plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/nrwl/nx/gh-issue-plan"><img src="https://agentmods.dev/badge/commands/nrwl/nx/gh-issue-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00857 |
| Opus 5.5 | $0.00000 | $0.00343 |
| Sonnet 5.5 | $0.00000 | $0.00171 |
| Haiku 4.5 | $0.00000 | $0.00086 |
Grade A, and why
gh-issue-plan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Issue Planning and Resolution
This command provides guidance for both automated and manual GitHub issue workflows.
Automated Workflow (GitHub Actions)
The automated workflow consists of two phases:
Phase 1: Planning (@claude plan or claude:plan label)
- Claude analyzes the issue and creates a detailed implementation plan
- Plan is posted as a comment on the issue
- Issue is labeled with
claude:planned
Phase 2: Implementation (@claude implement or claude:implement label)
- Claude implements the solution based on the plan
- Runs validation tests and creates a feature branch
- Suggests opening a PR with proper formatting
Planning Phase Template
When creating a plan (either automated or manual), include these sections:
Problem Analysis
- Root cause identification
- Impact assessment
- Related components or systems affected
Proposed Solution
- High-level approach
- Alternative solutions considered
- Trade-offs and rationale
Implementation Details
- Files that need to be modified
- Key changes required
- Dependencies or prerequisites
Testing Strategy
- Unit tests to add/modify
- Integration tests needed
- E2E test considerations
Validation Steps
# Test specific affected projects
nx run-many -t test,build,lint -p PROJECT_NAME
# Test all affected projects
nx affected -t build,test,lint
# Run affected e2e tests
nx affected -t e2e-local
# Format code
npx oxfmt FILES
# Final validation
pnpm nx prepush
Risks and Considerations
- Breaking changes
- Performance implications
- Migration requirements
Manual Workflow
When working on a GitHub issue manually, 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
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 156 lines · 0 tokens per session scan A 3dcbe3d04fb5
gh-issue-plan is a command published in the GitHub repository nrwl/nx (29,421 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 857 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.