github-agentic-workflows copilot-instructions.md

A project instruction file for a GitHub plugin that creates and maintains Agentic Workflows. These are Markdown workflow files that GitHub compiles into runnable YAML automation files.

In plain words
What is it for?
Use it to author, validate, update, review, merge, or report on GitHub Agentic Workflows.
Why use it?
It explains the repository layout, branching rules, and workflow format so an agent can edit the right source files and avoid changing generated files.

Instructions file for GitHub Copilot

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 instructions/zircote-plugins/github-agentic-workflows/copilot-instructions
Clone the repo
git clone --depth 1 https://github.com/zircote-plugins/github-agentic-workflows

Made for: GitHub Copilot.

Per session 1,587 This file is loaded in full into every session.
When invoked 1,587 The same file — it is already loaded in full.
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 $0.01587 $0.01587
Opus 5 $0.00794 $0.00794
Sonnet 5 $0.00317 $0.00317
Haiku 4.5 $0.00159 $0.00159

Measured yesterday against content hash 925e7bdeaa76, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

github-agentic-workflows copilot-instructions.md 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 yesterday.

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.

.github/copilot-instructions.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Copilot Instructions — aw-author Plugin

Project Identity

This is the aw-author Claude Code plugin (v1.3.0) for authoring, validating, and maintaining GitHub Agentic Workflow (gh-aw) markdown files. The repository lives at zircote/github-agentic-workflows.

gh-aw workflows are markdown files with YAML frontmatter in .github/workflows/, compiled to .lock.yml via gh aw compile. This plugin provides the reference materials, skills, and automated pipelines that keep those workflows correct and current.

Repository Structure

commands/              Slash command entry points (/aw-author, /aw-daily, /aw-merge, /aw-report, /aw-status, /aw-upgrade)
skills/
  aw-author/           Authoring skill + 9 reference files (the canonical gh-aw spec subset)
  aw-daily/            Autonomous daily pipeline skill + gap analysis references
  gh-aw-report/        Intelligence reporting skill + knowledge base + search queries
agents/
  aw-analyst.md        Deep analysis agent for workflow review
.github/workflows/
  daily-intelligence.md       Daily autonomous pipeline (gh-aw, fuzzy schedule)
  daily-intelligence.lock.yml Compiled workflow (DO NOT EDIT)
  weekly-develop-merge.md     Weekly develop→main merge (gh-aw, fuzzy schedule)
  weekly-develop-merge.lock.yml Compiled workflow (DO NOT EDIT)
outputs/gh-aw-reports/ Dated intelligence reports

Branching Strategy

  • main — stable, production branch
  • develop — daily automated updates land here via PR
  • daily-intelligence-YYYY-MM-DD — ephemeral feature branches created by /aw-daily, deleted after merge to develop
  • Weekly: develop merges to main via /aw-merge (squash merge, then develop resets to main)

Daily Pipeline (.github/workflows/daily-intelligence.md)

This workflow runs daily around 07:00 (fuzzy schedule) and executes:

  1. Research — web fetch + GitHub API queries on 5 tracked repos (github/gh-aw, github/github-mcp-server, github/copilot-cli, githubnext/agentics, zircote/github-agentic-workflows)
  2. Knowledge base update — append stable facts to skills/gh-aw-report/knowledge-base.md
  3. Discussion posting — post report to Discussions in the "Project News" category
  4. Gap analysis — compare findings against 11 reference files in skills/aw-author/references/ and skills/gh-aw-report/references/
  5. Issue creation — file issues for identified gaps (max 5 per run, dedup by [aw-daily] prefix)
  6. Implementation — edit reference files on a branch from develop
  7. PR creation — PR to develop with Closes #NNN links
  8. Summary — report what changed

Read the full file on GitHub · 112 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. yesterday First seen · 112 lines · 1,587 tokens per session scan A 925e7bdeaa76

Subscribe to this mod's changes

github-agentic-workflows copilot-instructions.md is an instructions file published in the GitHub repository zircote-plugins/github-agentic-workflows (2 stars, last pushed 1mo ago), licensed MIT. It adds 1,587 tokens to every session, about $0.0079 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 2026-08-31.

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