github-ci-fix-onboarding

A setup guide for using a coding agent to fix failed checks on GitHub pull requests. It prepares GitHub CLI access, a local copy of the repository, and the required tools.

In plain words
What is it for?
Use it when setting up or demonstrating GitHub CI fixing for the first time, or when a pull-request fix cannot start because its requirements are missing.
Why use it?
It helps remove setup problems before CI troubleshooting begins, such as missing login, permissions, repository files, or agent prerequisites.

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/tracer-cloud/opensre/github_ci_fix_onboarding
Any agent
npx skills add Tracer-Cloud/opensre --skill github_ci_fix_onboarding
Clone the repo
git clone --depth 1 https://github.com/Tracer-Cloud/opensre

Made for: Claude Code, Codex.

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,766 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 $0.00085 $0.02766
Opus 5 $0.00043 $0.01383
Sonnet 5 $0.00017 $0.00553
Haiku 4.5 $0.00009 $0.00277

Measured 2d ago against content hash 4979651d1d11, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

github-ci-fix-onboarding 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.

core/agent_harness/prompts/skills/github_ci_fix_onboarding/SKILL.md · 276 lines

How it starts

The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub CI/CD Onboarding & Installation

Goal

Get the user from zero to a working local CI/CD loop with zero friction. Treat every missing prerequisite as a task the skill must fix. Continue until one real, same-repository pull request has completed an end-to-end CI fix cycle and its required checks are green.

When to use

  • The user asks to set up, install, onboard, troubleshoot, or demo GitHub CI fixing in OpenSRE.
  • Action-shaped wording such as "Can you onboard me on the CI/CD flow?" means run this setup; it is not a request to explain the CI/CD documentation.
  • fix_github_pr_ci is unavailable or reports a missing CLI, token, checkout, permission, or coding-agent prerequisite.
  • The user asks to "fix CI on this PR" but first-time readiness is unknown.

Do not use this onboarding flow when prerequisites are already known to pass and the user only wants a CI failure fixed. Load github-ci-fix and call fix_github_pr_ci directly. Do not use it for an explicit explanation such as "How does the CI/CD flow work?" when the user did not ask to set up, install, onboard, demo, or fix anything.

Security rules

  • Never run gh auth status -t, gh auth token, env, or any command that prints a token.
  • Collect and persist the token only through the interactive GitHub integration setup prompt.
  • Do not claim that gh auth login alone configures OpenSRE. OpenSRE must also be able to resolve a token from its GitHub integration or supported environment.
  • Never manufacture a failing workflow for a demo, weaken CI, push to a protected branch, or use a fork PR. Use an existing same-repository PR with a genuine failing check.

Ownership rules

This flow is action-owned from the first prerequisite check to the completion report. Once loaded, drive every step with action tools and conclude with your own reply:

  • Keep this flow in the current agent turn — report progress, explain blockers, and summarize the final checks from the tool results. A generic answer does not know this workflow and will answer with unrelated GitHub status reads.
  • Never call engineering-status gather tools (generate_work_status_report, list_github_work_items, summarize_github_pr_status) here. Onboarding is not a status report.
  • When a prerequisite is blocked on the user (interactive login, PAT entry), conclude directly: state what passed, the exact command the user must run, and that you will rerun the failed check afterwards.
  • When all prerequisites pass, do not stop to summarize readiness — continue to the target-PR steps and fix_github_pr_ci in the same flow.

Read the full file on GitHub · 276 lines

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 · 276 lines · 85 tokens per session scan A 4979651d1d11

Subscribe to this mod's changes

github-ci-fix-onboarding is a skill published in the GitHub repository Tracer-Cloud/opensre (10,985 stars, last pushed today), licensed Apache-2.0. It adds 85 tokens to every session and 2,766 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.