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 instructions/agneym/generate-og-image/agents-mdgit clone --depth 1 https://github.com/agneym/generate-og-imageWrote 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/instructions/agneym/generate-og-image/agents-md)<a href="https://agentmods.dev/instructions/agneym/generate-og-image/agents-md"><img src="https://agentmods.dev/badge/instructions/agneym/generate-og-image/agents-md.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 | $0.00591 | $0.00591 |
| Opus 5 | $0.00296 | $0.00296 |
| Sonnet 5 | $0.00118 | $0.00118 |
| Haiku 4.5 | $0.00059 | $0.00059 |
Grade A, and why
generate-og-image AGENTS.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 5d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
This is a GitHub Action that generates Open Graph (OG) images from markdown files in pull requests. The action reads frontmatter configuration from .md/.mdx files and creates social media preview images using Puppeteer and a web component.
Development Commands
Build and Development
# Type checking
bun --bun tsc --noEmit
# Build for development
bun build src/main.ts --outdir dist --target node
# Build for release (compiled binary)
bun build src/main.ts --compile --outfile dist/index.js
# Run tests
bun test
# Format code
biome format --write
Code Quality
- Uses Biome for formatting and linting with tab indentation and double quotes
- Pre-commit hooks run
biome check --writevia lefthook - Type checking with TypeScript
Architecture
Core Flow (main.ts:17-56)
- Validates GitHub environment (PR context only)
- Gets repository configuration via
getRepoProps() - Finds markdown files in PR with
findFile() - For each file with OG config:
- Generates HTML template with
generateHtml() - Creates image using Puppeteer via
generateImage() - Commits the image file with
commitFile() - Posts preview comment (unless disabled)
- Generates HTML template with
Key Modules
- find-file.ts: Discovers markdown files in PR, filters by patterns, extracts frontmatter
- generate-image.ts: Uses Puppeteer with Chrome to screenshot HTML into base64 image
- file-filter.ts: Applies glob patterns to ignore specific files (default:
/README.md) - repo-props.ts: Merges GitHub Action inputs with defaults
- github-api.ts: Octokit client for GitHub API operations
Data Flow
- Input: Markdown files with
ogImagefrontmatter → File discovery & filtering → HTML generation → Image rendering → Git commit & comment
Docker Environment
- Runs in Docker container with Chrome executable at
/usr/bin/google-chrome-stable - Uses
action.ymlto define GitHub Action interface
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.
- 5d ago First seen · 71 lines · 591 tokens per session scan A b6285f2cd75f
generate-og-image AGENTS.md is an instructions file published in the GitHub repository agneym/generate-og-image (48 stars, last pushed 1y ago), licensed MIT. It adds 591 tokens to every session, about $0.0030 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.
Other instructions, from other repositories
run-gemini-cli GEMINI.md
Instructions for google-github-actions/run-gemini-cli, covering guidelines for developing this github action, core principles for this action and your role in development.
linkedin-content-engine CLAUDE.md
Claude Code instructions for mdbailin/linkedin-content-engine, covering claude implementation brief, goal, architecture constraints, required mcp tools and readbrandprofile.
docvideoer CLAUDE.md
Instructions for coding-ax/docvideoer, covering claude.md — docvideoer, 触发方式, 外部 skill 依赖, 工作目录 and 核心流水线(6 步).
ai-workflow-kit CLAUDE.md
Claude Code instructions for bezael/ai-workflow-kit, covering claude.md — ai workflow kit, what this repo is, where each tool reads skills from, available skills and specialized agents.
sound-effects-mcp CLAUDE.md
Claude Code instructions for sawa-zen/sound-effects-mcp, covering claude.md, プロジェクト概要, よく使うコマンド, 開発 and テスト.
mcp-svg-marp CLAUDE.md
Claude Code instructions for koppe-pan/mcp-svg-marp, covering mcp-svg-marp tool instructions, mcp tools available, 📊 convertsvgtomarp, 🔍 analyzesvg and automatic slide creation workflow.