ai-protocol AGENTS.md

A repository guide that tells AI coding agents which instructions to read and how to format and check their work. It uses AGENTS.md files to set rules for a project and its folders.

In plain words
What is it for?
Use it to define instruction format, discover the right guidance files, assign agent roles, and point agents to the project documents that apply to a task.
Why use it?
Without a shared guide, agents may miss local rules or make decisions that do not match the project’s agreed objectives. This provides one source of truth for agent-assisted work.

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/dnlbox/ai-protocol/agents-md
Clone the repo
git clone --depth 1 https://github.com/dnlbox/ai-protocol

Made for: Codex, OpenCode.

Per session 1,370 This file is loaded in full into every session.
When invoked 1,370 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 $0.01370 $0.01370
Opus 5 $0.00685 $0.00685
Sonnet 5 $0.00274 $0.00274
Haiku 4.5 $0.00137 $0.00137

Measured 2d ago against content hash e41229a0e990, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-protocol 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 · 166 lines

How it starts

The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file is the harness-agnostic contract for AI-assisted work in this repository.

The universal baseline ends at the Project Specifics marker.

The Project Specifics section defines how this repository applies the baseline.

Instruction format

  • Write one independently testable instruction per bullet.
  • Use the section heading to provide context.
  • Put rationale in a separate paragraph.
  • Put examples in a separate paragraph.
  • Keep each Markdown paragraph on one physical line.
  • Keep each Markdown list item on one physical line.

Instruction discovery

  • Read the nearest AGENTS.md before changing files.
  • Treat the nearest AGENTS.md as authoritative for its directory tree.
  • Load .agents/roles/leader.md when acting as the primary agent.
  • Load .agents/roles/teammate.md when accepting delegated work.
  • Load .agents/roles/adjudicator.md when reviewing a disputed or high-consequence decision.
  • Load a skill only when the user invokes it or its stated trigger applies.
  • Load only the project documents relevant to the approved objective.
  • Keep harness-specific instruction files as pointers to this contract.

Project truth

  • Treat docs/concept/ as accepted product intent.
  • Treat the Project Specifics section as the repository execution contract.
  • Treat BUILD_STATE.md as the latest verified repository checkpoint.
  • Treat executable evidence as authoritative for implemented behaviour.
  • Treat a runtime ledger as authoritative only for live worker state.
  • Treat conversation history as non-authoritative context.
  • Resolve contradictions in favour of the source that owns the disputed fact.
  • Surface unresolved authority conflicts to the user.

Approved objectives

  • Treat approval of a bounded implementation objective as authorization to complete that objective.
  • Plan the approved objective when no adequate plan exists.
  • Update the plan when implementation reveals new in-scope work.
  • Continue automatically after planning.
  • Continue automatically after an internal task completes.
  • Ask the user only when a decision would materially change product intent.
  • Ask the user only when a decision would materially expand scope.
  • Stop when required authority falls outside the approved objective.

Read the full file on GitHub · 166 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 · 166 lines · 1,370 tokens per session scan A e41229a0e990

Subscribe to this mod's changes

ai-protocol AGENTS.md is an instructions file published in the GitHub repository dnlbox/ai-protocol (18 stars, last pushed 23d ago), licensed MIT. It adds 1,370 tokens to every session, about $0.0068 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.