ci-e2e-time-tune

Calibrates E2E test time estimates from complete GitHub Actions CI logs.

2.3k|421|Updated Oct 9, 2025
One-click install
npx skills add https://github.com/radixark/miles --skill ci-e2e-time-tune
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ci-e2e-time-tune
Source: https://github.com/radixark/miles/tree/main/.claude/skills/ci-e2e-time-tune
Command: npx skills add https://github.com/radixark/miles --skill ci-e2e-time-tune

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

E2E test suites in CI pipelines rely on manually maintained est_time values that drift out of sync with actual runtimes, causing poor partition balancing and wasted CI capacity. This Skill tunes those literal register_cuda_ci(est_time=...) values using real evidence from complete GitHub Actions run logs.

Core Features & Use Cases

  • Evidence-backed runtime CSV: Parses complete job logs to produce an auditable CSV with per-file status, elapsed time, logged estimate, current estimate, and proposed estimate, citing exact log line numbers.
  • Deterministic estimate computation: Aggregates passed samples per test file across all jobs and partitions, applies a 1.25 safety factor, and rounds upward to 10-second or 100-second buckets.
  • Safe, estimate-only edits: Updates only literal est_time values in single register_cuda_ci(...) calls, never touching test logic, and never staging, committing, or pushing changes.
  • Use Case: After a nightly CI run, point the Skill at the run URL to recalibrate all tests/e2e timing estimates, review the generated CSV of raises and lowers, and leave the verified edits uncommitted in the working tree.

Quick Start

Tune the E2E time estimates in tests/e2e using the complete logs from this GitHub Actions run URL and show me the resulting CSV.

Frequently Asked Questions about ci-e2e-time-tune

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I tune E2E test time estimates from GitHub Actions logs?

Provide a GitHub Actions run URL, job URL, or a ci-fetch-log artifact directory. The Skill collects complete logs for every job, parses scheduled tests/e2e files and their outcomes, then computes and applies new est_time values with a 1.25 safety factor.

How are proposed est_time values calculated?

Passed rows are grouped by test file across all jobs and partitions. The maximum elapsed time is multiplied by 1.25 and rounded up: to the nearest 10 seconds at or below 200, or the nearest 100 seconds above 200. Failed or timed-out rows never contribute.

Can I use partial or filtered CI logs for timing calibration?

No. The Skill requires complete-run collection verified through a ci-fetch-log manifest with matching job-ID sets and log completeness flags. Filters may narrow the evidence view for the CSV and edits, but never narrow log collection itself.

Does the Skill commit or push the estimate changes?

No. It only edits literal est_time values in the working tree and explicitly never stages, commits, pushes, or opens a pull request. You review the diff and CSV before deciding to commit.

What happens when a test file has no passing evidence?

The file is marked skip in the CSV with no proposed estimate. Files with multiple register_cuda_ci calls, missing est_time, or non-literal computed values are also skipped rather than edited.

What if the CI logs come from a different commit than my checkout?

A head_sha mismatch is allowed when the logged commit is an ancestor of HEAD. Otherwise the Skill defaults to report-only mode, producing the CSV without edits unless you explicitly approve cross-revision changes.