payload-training-app AGENTS.md

Repository instructions for a Payload training application, including rules for when coding changes are allowed, where specifications and skills are kept, and how tasks should be routed.

In plain words
What is it for?
Use them when investigating or implementing features in the application, especially when checking specifications, loading skills, or synchronizing skill changes.
Why use it?
They help coding agents follow the project's approval process and local documentation before changing code, configuration, or other files.

Instructions file for CodexOpenCode

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/codee-sh/payload-training-app/agents-md
Clone the repo
git clone --depth 1 https://github.com/codee-sh/payload-training-app

Made for: Codex, OpenCode.

Per session 2,494 This file is loaded in full into every session.
When invoked 2,494 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 $0.02494 $0.02494
Opus 5 $0.01247 $0.01247
Sonnet 5 $0.00499 $0.00499
Haiku 4.5 $0.00249 $0.00249

Measured 2d ago against content hash dcd1b8885b1b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

payload-training-app 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 2d 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 · 211 lines

How it starts

The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Operational guide for AI agents working in this repository.


Before Writing Code

  • Write everything in English: code, comments, variable names, documentation.
  • Do not implement code, schema, migration, script, configuration, or documentation changes unless the user explicitly authorizes implementation with "wdrażamy" or an equivalent clear instruction. Analysis, investigation, and recommendations do not authorize changes.
  • Check .ai/specs/ before coding any non-trivial feature.
  • Skills are installed in .claude/skills/ (Claude Code) and .agents/skills/ (Codex). .agents/skills/ is the local source of truth — edit a skill only there, then run ags push-skill to propagate it to the source repo (it also syncs the .claude/skills/ copy). See Installing skills.
  • Prefer minimal, focused changes. Do not refactor code outside the task scope.
  • Do not run yarn build automatically after implementation. Run it only when the user explicitly asks.
  • Comment and naming conventions are defined in the code-style skill. Load it before writing or reviewing TypeScript.

Task Router

Match the task to the table before starting. A single task often maps to multiple rows.

Task Action
Creating a new collection or extending the schema Load skill payload-build-collections
Adding a custom admin view, tab, or field UI Load skill payload-build-modules
Building a front-end component or page (src/components, src/modules/*/components, (frontend)) Load skill payload-frontend-build-components
Debugging hooks, queries, access control, transactions Load skill payload
Security review, or adding/modifying auth, access control, uploads, CORS/CSRF, headers Load skill payload-security; keep .ai/audits/security-audit.md current
Writing questions for a client or stakeholder Load skill writing-questions
Starting a new spec or reviewing one Load skill spec-writing
Any TypeScript code Load skill code-style

Read the full file on GitHub · 211 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. 2d ago First seen · 211 lines · 2,494 tokens per session scan A dcd1b8885b1b

Subscribe to this mod's changes

payload-training-app AGENTS.md is an instructions file published in the GitHub repository codee-sh/payload-training-app (11 stars, last pushed 20d ago), licensed MIT. It adds 2,494 tokens to every session, about $0.0125 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.

Related

Other instructions, from other repositories