Agent skill

CI Failure Analysis

by vortex-data in vortex-data/vortex

Analyze Vortex GitHub Actions CI failures. An agent skill from vortex-data/vortex.

Apache-2.0Auto-check passedTesting & QA

Install CI Failure Analysis

skills CLI
$ npx skills add vortex-data/vortex --skill ci-failure-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install vortex-data/vortex ci-failure-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/vortex-data/vortex.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/ci-failure-analysis .claude/skills/ci-failure-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ci-failure-analysis
GitHub stars
3.2k
Token cost
~810 tokens
SKILL.md length
289 words
Files
1
Skills in repo
3
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyze Vortex GitHub Actions CI failures. An agent skill from vortex-data/vortex.

  • Works in 7 steps: List failed jobs for the workflow run → Fetch only failed job logs first → If any gh command fails with error… → …
  • Asked to investigate failed CI runs
  • SKILL.md covers Inputs, Workflow, Report Format and Rules
  • Calls gh, cargo and make

What it does

CI Failure Analysis is an agent skill from vortex-data/vortex. Analyze Vortex GitHub Actions CI failures. Use when asked to investigate failed CI runs, failed jobs, or when the user mentions "/ci-failure-analysis".

Its SKILL.md is about 810 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering Failing and flaky tests. It works with GitHub Actions, Rust and Python. The repository describes itself as: An extensible, state-of-the-art framework for columnar compression, and the fastest FOSS columnar file format. Formerly at @spiraldb, now an Incubation Stage project at… The licence is Apache-2.0.

When your agent uses it

  • Asked to investigate failed CI runs
  • The user mentions /ci-failure-analysis

Example prompts

  • “/ci-failure-analysis”
  • “/ci-failure-analysis”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. List failed jobs for the workflow run
  2. Fetch only failed job logs first
  3. If any gh command fails with error connecting to api.github.com in a sandbox, rerun it with
  4. Classify each failure
  5. Fetch the PR diff and metadata only after the failing log section is understood
  6. Reproduce narrowly when practical
  7. Check whether the same failure appears on recent main-branch runs or open issues before calling

What it can do on your machine

Read from SKILL.md and the folder at commit d9ad4cf. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • gh
    • cargo
    • make
    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use gh and uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

CI Failure Analysis loads about 810 tokens when it runs. Until then it costs about 43 tokens; SKILL.md has 289 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~43
When it runs · the whole SKILL.md, loaded when a task matches
~810

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from vortex-data/vortex at commit d9ad4cf, republished under its Apache-2.0 licence (© vortex-data). 289 words, ~810 tokens.

Download SKILL.mdSave it as .claude/skills/ci-failure-analysis/SKILL.md (or your agent's skills folder).
name
ci-failure-analysis
description
Analyze Vortex GitHub Actions CI failures. Use when asked to investigate failed CI runs, failed jobs, or when the user mentions "/ci-failure-analysis".

Vortex CI Failure Analysis Skill

Analyze failed GitHub Actions runs for the Vortex repository and identify whether the failure is caused by the PR, pre-existing flakiness, infrastructure, or an unrelated main-branch issue.

Inputs

Use any PR number, repository, run ID, failed job metadata, or log snippets supplied by the user or automation prompt. If a needed value is missing, discover it with the narrowest gh command that can answer the question.

Workflow

  1. List failed jobs for the workflow run:

    bash
    gh run view <run-id> --repo <owner/repo> --json jobs
  2. Fetch only failed job logs first:

    bash
    gh run view <run-id> --repo <owner/repo> --job <job-id> --log-failed

    If that fails, use the Actions API:

    bash
    gh api repos/<owner/repo>/actions/jobs/<job-id>/logs
  3. If any gh command fails with error connecting to api.github.com in a sandbox, rerun it with escalated network permissions immediately.

  4. Classify each failure:

    • Rust build errors: compiler diagnostics, spans, trait bound failures, feature-gate issues.
    • Rust test failures: failing test name, panic/assertion output, expected vs actual values, source path and line.
    • Clippy failures: lint name, file path, line, and suggested fix if shown.
    • Formatting or public API failures: changed files and commands needed to regenerate output.
    • Python/docs failures: pytest, maturin, Sphinx, doctest, or packaging output.
    • Infrastructure failures: toolchain download, cache, runner, network, disk, timeout, or service issues.
  5. Fetch the PR diff and metadata only after the failing log section is understood:

    bash
    gh pr view <pr-number> --repo <owner/repo> --json title,body,baseRefName,headRefName,files,commits
    gh pr diff <pr-number> --repo <owner/repo>
  6. Reproduce narrowly when practical:

    bash
    cargo test -p <crate-name> <test-name>
    cargo clippy -p <crate-name> --all-targets --all-features
    make -C docs doctest
    uv run --all-packages pytest <path>
  7. Check whether the same failure appears on recent main-branch runs or open issues before calling it PR-caused.

Report Format

Post or return one concise Markdown report:

markdown
## CI Failure Analysis

### Status
<PR-caused | likely pre-existing | infrastructure | inconclusive>

### Failed Jobs
- `<job name>`: <build | test | clippy | fmt | docs | infra>

### Relevant Log Output
```text
<only the failing lines needed to understand the issue>
```

### Correlation With PR Changes
<Explain whether the diff touches the failing area and cite files/functions.>

### Recommended Next Step
<One or two concrete commands or code fixes.>

Rules

  • Show relevant failure excerpts, not full logs.
  • If many tests fail, detail the first few distinct failures and summarize the rest.
  • Do not guess. If causation is unclear, say what was checked and what would resolve it.
  • Prefer one PR comment or one final report over multiple fragmented updates.

© vortex-data, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/ci-failure-analysis of vortex-data/vortex.

Open the folder on GitHubat commit d9ad4cf

Compare with similar skills

CI Failure Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

CI Failure Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
CI Failure Analysis this skillvortex-data/vortex3.2k—~810Automated safety check: PassApache-2.0
Apple Container Test RunnerRustPython/RustPython22k—~467Automated safety check: PassMIT
GreptimeDB Fuzz CI Failure InvestigationGreptimeTeam/greptimedb6.7k—~4.4kAutomated safety check: PassApache-2.0
RustPython Test Failure InvestigationRustPython/RustPython22k—~467Automated safety check: PassMIT
Manor CI Triagemanor-os/manor-ai161—~533Automated safety check: PassCustom licence
RustPython Stdlib UpgradeRustPython/RustPython22k—~876Automated safety check: PassMIT

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Categories

Questions about CI Failure Analysis

What does CI Failure Analysis do?

Analyze Vortex GitHub Actions CI failures. An agent skill from vortex-data/vortex. CI Failure Analysis is an agent skill from vortex-data/vortex. Analyze Vortex GitHub Actions CI failures.

When should I use CI Failure Analysis?

CI Failure Analysis fits situations like: asked to investigate failed CI runs; the user mentions /ci-failure-analysis.

How do I install CI Failure Analysis in Claude Code?

Run `npx skills add vortex-data/vortex --skill ci-failure-analysis -a claude-code`. Or copy the skill folder (.agents/skills/ci-failure-analysis in vortex-data/vortex) into .claude/skills/ci-failure-analysis in your project. Claude Code loads it when a task matches its description.

How do I install CI Failure Analysis in Codex?

Run `npx skills add vortex-data/vortex --skill ci-failure-analysis -a codex`. Or copy the skill folder (.agents/skills/ci-failure-analysis in vortex-data/vortex) into .agents/skills/ci-failure-analysis in your project. Codex loads it when a task matches its description.

Can I use CI Failure Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vortex-data/vortex --skill ci-failure-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ci-failure-analysis, .gemini/skills/ci-failure-analysis, .github/skills/ci-failure-analysis and .opencode/skills/ci-failure-analysis in your project.

What does CI Failure Analysis need to run?

Going by SKILL.md and its folder, CI Failure Analysis needs the command-line tools its instructions call (gh, cargo, make and uv).

Does CI Failure Analysis access the network?

SKILL.md contains no URLs. Its commands use gh and uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is CI Failure Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does CI Failure Analysis use?

CI Failure Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does CI Failure Analysis use?

About 810 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to CI Failure Analysis?

Skills that share tags, products or a category with CI Failure Analysis: Apple Container Test Runner (RustPython/RustPython, 22k stars), GreptimeDB Fuzz CI Failure Investigation (GreptimeTeam/greptimedb, 6.7k stars), RustPython Test Failure Investigation (RustPython/RustPython, 22k stars) and Manor CI Triage (manor-os/manor-ai, 161 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains CI Failure Analysis?

vortex-data (a GitHub organization) maintains it in vortex-data/vortex, which has 3,248 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 7, 2026.

Source: vortex-data/vortex on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.