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.
npx agentmods add skills/hack23/european-parliament-mcp-server/github-agentic-workflowsnpx skills add Hack23/European-Parliament-MCP-Server --skill github-agentic-workflowsgit clone --depth 1 https://github.com/Hack23/European-Parliament-MCP-ServerWrote 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/skills/hack23/european-parliament-mcp-server/github-agentic-workflows)<a href="https://agentmods.dev/skills/hack23/european-parliament-mcp-server/github-agentic-workflows"><img src="https://agentmods.dev/badge/skills/hack23/european-parliament-mcp-server/github-agentic-workflows.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.02636 |
| Opus 5 | $0.00021 | $0.01318 |
| Sonnet 5 | $0.00008 | $0.00527 |
| Haiku 4.5 | $0.00004 | $0.00264 |
Grade A, and why
github-agentic-workflows scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads MCP configurationlowAgent snooping
mcp.json carries server URLs and auth tokens; reading it lets a mod discover and abuse other integrations.
MCP server configuration is defined in `.github/copilot-mcp.json`. Secret references (`${{ secrets.* }}`) are resolved by the Copilot runtime. See `.github/copilot-mcp.json` for the canonical configuration. Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Agentic Workflows Skill
Purpose
Comprehensive guidance for GitHub Agentic Workflows (gh-aw) — a Go-based GitHub CLI extension that enables writing agentic workflows in natural language using markdown files, compiled into GitHub Actions workflows with defense-in-depth security. Also covers Copilot coding agent orchestration, MCP server configuration, stacked PRs, and OWASP Agentic security.
When to Use
- ✅ Writing markdown-defined AI workflows (
gh-aw) for automated repository tasks - ✅ Orchestrating Copilot coding agent assignments with
base_refandcustom_instructions - ✅ Building multi-step agentic workflows with stacked PRs
- ✅ Configuring safe outputs, permissions, and AI engine selection
- ✅ Securing agentic pipelines against prompt injection and data exfiltration
- ✅ Implementing Continuous AI patterns (scheduled + event-triggered AI automation)
GitHub Agentic Workflows (gh-aw)
Overview
GitHub Agentic Workflows (gh-aw) augments deterministic CI/CD with Continuous AI — systematic, automated application of AI to software collaboration. Workflows are defined in markdown with YAML frontmatter and compiled to GitHub Actions via gh aw compile.
Key capabilities: Issue triage, CI failure diagnosis, documentation maintenance, code quality improvement, metrics/analytics, security scanning, multi-repo coordination, project planning.
Workflow Definition Format
---
timeout-minutes: 5
on:
schedule: daily # or cron: "0 9 * * 1-5", or event triggers
issue:
types: [opened, reopened]
permissions:
contents: read
issues: read
pull-requests: read
tools:
github:
toolsets: [issues, labels, pull_requests, repos]
safe-outputs:
create-issue:
title-prefix: "[report] "
labels: [automated, report]
close-older-issues: true
add-labels:
allowed: [bug, feature, enhancement, documentation]
add-comment: {}
create-pull-request:
title-prefix: "[auto] "
max-changed-files: 5
---
# Workflow Title
Natural language instructions for the AI agent describing what to do.
## Context
- Repository-specific guidance
- What to analyze or act on
## Rules
- Constraints and boundaries
- Output format requirements
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.
- 6d ago First seen · 270 lines · 42 tokens per session scan A 9c0e6234eeef
github-agentic-workflows is a skill published in the GitHub repository Hack23/European-Parliament-MCP-Server (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 42 tokens to every session and 2,636 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (reads mcp configuration). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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