Nx Console is an editor interface for Nx and Lerna monorepos, which are code repositories containing multiple related projects managed together. It gives developers visual workflows for viewing workspace structure, running tasks, navigating task graphs, and supplying workspace context to AI tools. The catalogue entries extend its workflows through skills, agents, instructions, MCP integrations, settings, and commands.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nrwl/nx-console/nx-pluginsnpx skills add nrwl/nx-console --skill nx-pluginsgit clone --depth 1 https://github.com/nrwl/nx-consoleWrote 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/skills/nrwl/nx-console/nx-plugins)<a href="https://agentmods.dev/skills/nrwl/nx-console/nx-plugins"><img src="https://agentmods.dev/badge/skills/nrwl/nx-console/nx-plugins.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.00083 |
| Opus 5 | $0.00018 | $0.00042 |
| Sonnet 5 | $0.00007 | $0.00017 |
| Haiku 4.5 | $0.00004 | $0.00008 |
Grade A, and why
nx-plugins 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 5d 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.
This is a copy
100% identical to nx-plugins — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Finding and Installing new plugins
- List plugins:
pnpm nx list - Install plugins
pnpm nx add <plugin>. Example:pnpm nx add @nx/react.
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.
- 5d ago First seen · 10 lines · 37 tokens per session scan A 96659fc0ea92
nx-plugins is a skill published in the GitHub repository nrwl/nx-console (1,412 stars, last pushed 2d ago), licensed MIT. It adds 37 tokens to every session and 83 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to nx-plugins, differing in 0 lines, and is treated as a copy.
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…