audit-ci

A workflow for measuring and analyzing the time taken by cold CI, meaning continuous integration started without reusable cached results.

In plain words
What is it for?
Use it to profile pnpm CI runs, inspect existing performance reports, compare timings, and propose evidence-based improvements to builds, tests, linting, or dependency handling.
Why use it?
It shows what controls total build and test time and helps distinguish real bottlenecks from guesses.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/nvidia/elements/audit-ci
Any agent
npx skills add NVIDIA/elements --skill audit-ci
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/elements

Made for: Claude Code, Codex.

Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,411 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00078 $0.01411
Opus 5 $0.00039 $0.00705
Sonnet 5 $0.00016 $0.00282
Haiku 4.5 $0.00008 $0.00141

Measured 2d ago against content hash e8050249f9a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

audit-ci 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 2d 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.

.agents/skills/audit-ci/SKILL.md · 139 lines

How it starts

The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Audit CI

Produce a repeatable cold-CI profile, explain what controls wall-clock completion, and turn the evidence into prioritized, testable recommendations.

Required context

  1. Read the repository AGENTS.md.
  2. Read projects/internals/BUILD.md.
  3. Inspect the current root ci:profile script and projects/internals/ci/ci-profile.js. Treat the script as the profiling source of truth.
  4. Read a project's DEVELOPMENT.md before running project-specific commands when that file exists.

Do not copy profiling logic into this skill. Update the repository profiler when its behavior needs to change.

Choose the workflow

  • Run a new profile when the user asks to rerun, benchmark current changes, refresh an audit, or verify an optimization.
  • Analyze existing .metrics/ci-profile.{json,md} artifacts without rerunning when the user asks only for interpretation and the artifacts match the intended commit and worktree state.
  • Create recommendations without implementing them unless the user also asks for the changes.

Profile safely

Run all repository commands through mise.

  1. Inspect git status --short.

  2. Preview ignored files that reset would delete with git clean -ndX.

  3. Stop and ask before profiling if that preview includes user data, local assets, secrets, or other non-reproducible files. The profiler runs pnpm run ci:reset, which deletes ignored files and reinstalls dependencies before every sample.

  4. Never stash, commit, discard, or clean tracked changes merely to make the profiler accept the worktree.

  5. Use the clean command when the worktree is clean:

    mise exec -- pnpm run ci:profile
    
  6. When the dirty changes are the intentional subject of the audit, preserve them and run:

    CI_PROFILE_ALLOW_DIRTY=1 mise exec -- pnpm run ci:profile
    

    Record the dirty-worktree condition in the report. Do not use this override for unrelated or unexplained changes.

Allow all three cold samples to finish. Dependency installation or browser setup can require network access. If a run fails, inspect the copied .metrics/ci-profile-run-*.log and reset logs, report the incomplete profile, and do not invent missing samples.

Read the full file on GitHub · 139 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 2d ago First seen · 139 lines · 78 tokens per session scan A e8050249f9a1

Subscribe to this mod's changes

audit-ci is a skill published in the GitHub repository NVIDIA/elements (83 stars, last pushed 2d ago), licensed Apache-2.0. It adds 78 tokens to every session and 1,411 once invoked, about $0.0004 per session on Opus 5. 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.

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