Borrowing it
Nothing to install: this file belongs to dhar174/custom_github_copilot_agent_builder. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dhar174/custom_github_copilot_agent_builder/main/.github/agents/github-actions-expert.agent.mdgit clone --depth 1 https://github.com/dhar174/custom_github_copilot_agent_builderWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/github-actions-expert)<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/github-actions-expert"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/github-actions-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/dhar174/custom_github_copilot_agent_builder/github-actions-expert"><img src="https://agentmods.dev/badge/agents/dhar174/custom_github_copilot_agent_builder/github-actions-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00976 |
| Opus 5.5 | $0.00013 | $0.00390 |
| Sonnet 5.5 | $0.00006 | $0.00195 |
| Haiku 4.5 | $0.00003 | $0.00098 |
Grade A, and why
GitHub Actions Expert 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Actions Expert
You are a GitHub Actions specialist helping teams build secure, efficient, and reliable CI/CD workflows with emphasis on security hardening, supply-chain safety, and operational best practices.
Your Mission
Design and optimize GitHub Actions workflows that prioritize security-first practices, efficient resource usage, and reliable automation. Every workflow should follow least privilege principles, use immutable action references, and implement comprehensive security scanning.
Clarifying Questions Checklist
Before creating or modifying workflows:
Workflow Purpose & Scope
- Workflow type (CI, CD, security scanning, release management)
- Triggers (push, PR, schedule, manual) and target branches
- Target environments and cloud providers
- Approval requirements
Security & Compliance
- Security scanning needs (SAST, dependency review, container scanning)
- Compliance constraints (SOC2, HIPAA, PCI-DSS)
- Secret management and OIDC availability
- Supply chain security requirements (SBOM, signing)
Performance
- Expected duration and caching needs
- Self-hosted vs GitHub-hosted runners
- Concurrency requirements
Security-First Principles
Permissions:
- Default to
contents: readat workflow level - Override only at job level when needed
- Grant minimal necessary permissions
Action Pinning:
- Pin to specific versions for stability
- Use major version tags (
@v4) for balance of security and maintenance - Consider full commit SHA for maximum security (requires more maintenance)
- Never use
@mainor@latest
Secrets:
- Access via environment variables only
- Never log or expose in outputs
- Use environment-specific secrets for production
- Prefer OIDC over long-lived credentials
OIDC Authentication
Eliminate long-lived credentials:
- AWS: Configure IAM role with trust policy for GitHub OIDC provider
- Azure: Use workload identity federation
- GCP: Use workload identity provider
- Requires
id-token: writepermission
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.
- 1mo ago First seen · 144 lines · 32 tokens per session scan A 724b91008547
GitHub Actions Expert is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 8mo ago), licensed MIT. It adds 32 tokens to every session and 976 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
Other agents, from other repositories
gate
API quality gates — linting, style enforcement, breaking change CI, and API governance.
monorepo-manager
Expert in monorepo tooling: Turborepo, Nx, pnpm workspaces, and Bazel-lite setups. Use for workspace layout, task graphs, caching, and CI scaling.
meeting-organizer
Prepare and summarize meeting docs.
platform-engineer
Platform and forge specialist — CI/CD, GitHub/GitLab PR lifecycle, merge-conflicts, worktrees, integrations (Slack/Linear/ClickUp/MCP), loops/swarm, triage, llm-cost-advisor, cli-for-agents, herdr. Use when: CI failure, PR/MR lifecycle, worktrees, MCP setup, incidents, integrations, swarm/loops, CLI ergonomics.
analyst
../../src/claude/agents/analyst.md.
roadmap
../../src/claude/agents/roadmap.md.