self-media-content-workflow: Instructions file for Codex

AGENTS.md

self-media-content-workflow AGENTS.md is an instructions file for Codex, OpenCode from yanhua1010/self-media-content-workflow. It costs 226 tokens per session, scanned A, original, MIT.

Repository instructions are written guidance that tells a coding agent how to work in a specific code project.

In plain words
What is it for?
They help maintain reusable Skills, check changes with validation scripts, protect secrets and private data, and create focused conventional commits.
Why use it?
They keep files, workflows, security practices, validation, and commits consistent instead of leaving those decisions to guesswork.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is yanhua1010/self-media-content-workflow's own configuration. It tells Codex and OpenCode how to work on self-media-content-workflow itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything self-media-content-workflow configures →

Reuse

Borrowing it

Nothing to install: this file belongs to yanhua1010/self-media-content-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/yanhua1010/self-media-content-workflow/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/yanhua1010/self-media-content-workflow

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for self-media-content-workflow AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/yanhua1010/self-media-content-workflow/agents-md/github.svg)](https://agentmods.dev/instructions/yanhua1010/self-media-content-workflow/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/yanhua1010/self-media-content-workflow/agents-md"><img src="https://agentmods.dev/badge/instructions/yanhua1010/self-media-content-workflow/agents-md/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.

agentmods 80×15 button for self-media-content-workflow AGENTS.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/yanhua1010/self-media-content-workflow/agents-md"><img src="https://agentmods.dev/badge/instructions/yanhua1010/self-media-content-workflow/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 226 This file is loaded in full into every session.
When invoked 226 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00226 $0.00226
Opus 5 $0.00113 $0.00113
Sonnet 5 $0.00045 $0.00045
Haiku 4.5 $0.00023 $0.00023

Measured 9d ago against content hash 1737e5db217b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

self-media-content-workflow 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 9d 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.

AGENTS.md · 32 lines

What it actually says

Repository instructions

Scope

This repository contains a tool-agnostic self-media Skill suite. Keep reusable workflows in SKILL.md, detailed platform guidance in references/, and copyable output templates in assets/.

Rules

  • Keep every SKILL.md below 500 lines.
  • Use only name and description in Skill frontmatter.
  • Keep exact platform limits out of core instructions unless they are verified and time-stamped.
  • Do not bind core Skills to a single model, browser, image provider, publisher, or analytics service.
  • Do not add credentials, Cookie examples, private URLs, real user data, or secrets.
  • Treat research tools as read-only by default.
  • Require explicit user authorization before external write actions.
  • Keep multi-platform outputs native to each platform.
  • Add or update templates when a workflow introduces a required deliverable.

Validation

Run:

python3 scripts/validate.py

Also run the system Skill validator when available.

Commits

Use conventional commits with a clear module scope. Do not stage unrelated files.

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. 9d ago First seen · 32 lines · 226 tokens per session scan A 1737e5db217b

Subscribe to this mod's changes

self-media-content-workflow AGENTS.md is an instructions file published in the GitHub repository yanhua1010/self-media-content-workflow (477 stars, last pushed 17d ago), licensed MIT. It adds 226 tokens to every session, about $0.0011 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.

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