Nx Cloud Ci Failure Review logo

Nx Cloud Ci Failure Review

Organization
nrwl
nx-cloud-ci-failure-review

Review failed Nx Cloud CI pipeline executions and group recurring, evidence-based failure patterns. Use this skill whenever a user asks about failed CI pipelines, recurring task failures, failed CIPEs, a CI failure review, or a last-24-hours CI report. Use the nx-cloud-api skill for every Nx Cloud read. This read-only skill separates task, workflow, agent, timeout, cancellation, and unknown cases. It suggests diagnostic next steps without changing systems.

Overview

Publishernrwl
Repositorynx-ai-agents-config
Skill namenx-cloud-ci-failure-review
Stars
28
Forks
8
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 nrwl on GitHub. Read the source before you install it.

Installation

Install the Nx Cloud Ci Failure Review 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.
    https://github.com/nrwl/nx-ai-agents-config/tree/main/generated/.agents/skills/nx-cloud-ci-failure-review
  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/nrwl/nx-ai-agents-config.git /tmp/nx-ai-agents-config
mkdir -p .claude/skills
cp -r /tmp/nx-ai-agents-config/generated/.agents/skills/nx-cloud-ci-failure-review .claude/skills/nx-cloud-ci-failure-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nx Cloud Ci Failure Review 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 Nx Cloud Ci Failure Review 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 Nx Cloud Ci Failure Review 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.

Nx Cloud CI failure review

Requires the nx-cloud-api skill for all Nx Cloud reads. This workflow is read-only.

Reduce failed pipelines to a small set of diagnostic groups. A failed pipeline does not prove that an agent or platform caused the failure. Classify each group only at the level the evidence supports.

Scope and collection

Use focused investigation mode when the user supplies one or more CIPE or run-group links. Fetch those exact records first. Follow their returned run-group, run, task, and workflow links. Compare the supplied executions directly. Do not run a broad time window or build a workspace-wide ranking unless the user asks for recurrence or scope. Keep cancellations that follow the named critical error as consequences, not separate root-cause groups.

Use review mode when the user asks for a workspace failure review. Review failures from the last 24 hours by default. CIPE and run-group list filters use createdAt, not failure time. Query a 30-hour creation window to cover the maximum normal six-hour CI duration. State the intended 24-hour review period and the 30-hour creation window.

Query statuses=FAILED, statuses=TIMED_OUT, and statuses=CANCELED (the cipes filter accepts only terminal statuses). State the branches, CI contexts, statuses, endpoints, and record counts. Ask before widening the window or mixing unrelated repositories/workspaces.

Use nx-cloud-api (npx nx-cloud api) for every read. Inspect the live schemas with --describe for cipes, run-groups, run-groups/{runGroupId}, runs, runs/{runId}/tasks, and the linked steps and instances endpoints. Use --list-operations to confirm the routes; the public API has no separate workflow routes. Reach child records by following returned links. Start with supplied CIPEs in focused investigation mode. Start with failed CIPEs and their linked run groups in review mode. Use only live documented filters and fields. Fetch one narrow page first and check nextCursor before continuing.

Collect in this order:

  1. Failed, timed-out, and canceled CIPEs with status, timestamps, branch, and CI context. Use a small, stated --pages value. Rank groups workspace-wide only after a zero exit with nextCursor: null; otherwise report the data as incomplete.
  2. Linked run groups and their documented critical-error fields.
  3. Runs and terminal task rows for each selected group.
  4. Workflow and instance status only when task data does not explain the group.
  5. The smallest relevant task or instance log excerpt for representative cases.

Use a semaphore of at most five narrow detail requests. Fetch logs only after a group reaches the top five. Tell the user before reading CI log content. Quote only redacted error lines.

Treat cancellations as their own category until their reason and timing show that they belong elsewhere. Do not call a cancellation a failure without that context.

Grouping method

Build groups from stable evidence. Prefer a task identifier plus normalized error signature. Normalize timestamps, GUIDs, retry counters, temporary paths, and random ports. Keep stack context, command, and error code that distinguish two otherwise similar messages.

Use these categories only when their evidence exists:

  • Repeated task error.
  • Task timeout.
  • Cancellation.
  • Workflow or agent failure.
  • Unknown pipeline failure.

Call a group workflow or agent failure only when workflow/instance status, critical error, or agent evidence supports it and no task failure explains the pipeline. Do not infer infrastructure from the absence of a task log.

Reconcile the full pipeline picture before classification. A task can record SUCCEEDED or a cache hit while the main job fails during artifact download, validation, or restoration. Compare the run-group criticalErrorMessage, task status, cache status, workflow status, and later cancellations. In that case, classify the main-job cache restoration error as primary and the canceled runs as consequences.

For every group, record its CIPE count, run-group count, affected task count, first and last occurrence, branches/contexts, and one or two representative IDs. Rank first by affected pipeline count, then recurrence, then blocked duration when it is documented.

Next action rules

  • Repeated task error: when a relevant workspace checkout exists, inspect CODEOWNERS and project ownership metadata at the recorded commit. Suggest a likely review owner. Do not assign work or claim ownership when that evidence is absent.
  • Task timeout: compare duration and resource evidence. Request a focused reproduction or resource report when it does not show a direct cause.
  • Cancellation: identify the documented cancel source, or keep it separate as unknown cancellation.
  • Workflow or agent failure: retry or monitor only when the evidence supports a transient event. Otherwise inspect the named workflow/agent asset.
  • Unknown: request the smallest log or run detail that can separate the cases.

Do not make code, workflow, or allocation changes without explicit approval.

Report format

md
# Failed CI review

## Scope

- Window: …
- Data: …

## Failure groups

### 1. <evidence-level category> — <short signature>

- **Confirmed facts:** affected CIPEs/runs/tasks; representative IDs; log excerpt.
- **Assessment:** **Confirmed** / **Likely** / **Needs diagnostic run** — …
- **Impact:** …
- **Highest-leverage next action:** …

## Unclassified or incomplete data

- …

Limit a review report to five groups. In focused investigation mode, report the supplied executions as one comparison when they have the same normalized signature. Link each finding to exact CIPEs, run groups, runs, and tasks where available. State the data limit when pagination, missing assets, or missing context affects the conclusion.

Frequently asked questions

What does the Nx Cloud Ci Failure Review AI skill do?

Review failed Nx Cloud CI pipeline executions and group recurring, evidence-based failure patterns. Use this skill whenever a user asks about failed CI pipelines, recurring task failures, failed CIPEs, a CI failure review, or a last-24-hours CI report. Use the nx-cloud-api skill for every Nx Cloud read. This read-only skill separates task, workflow, agent, timeout, cancellation, and unknown cases. It suggests diagnostic next steps without changing systems.

Why use Nx Cloud Ci Failure Review on TypingMind?

Because you install it once and use it with any model. Nx Cloud Ci Failure Review 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 Nx Cloud Ci Failure Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nrwl/nx-ai-agents-config/tree/main/generated/.agents/skills/nx-cloud-ci-failure-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nx Cloud Ci Failure Review?

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 Nx Cloud Ci Failure Review?

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

Is the Nx Cloud Ci Failure Review AI skill free?

Yes. It is published on GitHub by nrwl 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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