vale-ai-tells: Instructions file for Codex

AGENTS.md

vale-ai-tells AGENTS.md is an instructions file for Codex, OpenCode from tbhb/vale-ai-tells. It costs 967 tokens per session, scanned A, original, MIT.

A repository instruction guide for coding agents working on Vale AI Tells, a package that checks prose for AI-associated language patterns. It covers commit messages, linting, repository rules, and document drafting.

In plain words
What is it for?
Preparing valid commits, running the repository's message and prose checks, following agent instructions, and drafting project documentation.
Why use it?
It makes the required contribution process explicit, including commit format, sign-off, validation checks, and where to draft messages before committing.

Instructions file for CodexOpenCode

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

This is tbhb/vale-ai-tells's own configuration. It tells Codex and OpenCode how to work on vale-ai-tells 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 vale-ai-tells configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tbhb/vale-ai-tells. 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/tbhb/vale-ai-tells/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/tbhb/vale-ai-tells

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 967 This file is loaded in full into every session.
When invoked 967 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 $0.00967 $0.00967
Opus 5 $0.00483 $0.00483
Sonnet 5 $0.00193 $0.00193
Haiku 4.5 $0.00097 $0.00097

Measured 2d ago against content hash a6e2d12a3bb2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

vale-ai-tells 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 · 34 lines

How it starts

The opening of the file, as written. The whole thing — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent instructions

Guidance for AI coding agents working in this repository. Read it alongside the per-tool documentation and any memory files the harness loads.

Commit messages

Write Conventional Commits (type(scope): subject) with a DCO Signed-off-by trailer, and keep the subject under 80 characters. AI assistance is credited with a kernel-style Assisted-by: AGENT:VERSION [TOOL] trailer placed before the sign-off. Never credit a model through Co-authored-by.

Draft every message in a repo-root COMMIT_AGENTMSG file before you run git commit. A gitignore entry keeps that file out of history, so it serves purely as a scratchpad:

  1. Write the full message (subject, body, and trailers) to COMMIT_AGENTMSG.
  2. Run mise run lint-commit-msg and resolve whatever it reports.
  3. Commit the validated draft with git commit -s -F COMMIT_AGENTMSG.

The commit-msg stage runs four hooks from the shared repotools repository: commitlint (the Conventional Commits format and length bounds), commit-trailers (the trailer format and order), vale-commit-msg (prose, under this repo's own ai-tells and ai-tells-commits styles), and cspell-commit-msg (spelling). Run mise run repotools:prek-install once so the hooks run on every commit.

That hook stage is the real gate. mise run lint-commit-msg only previews it, so a clean recipe run predicts a clean commit without replacing the hook.

Prose lint output

The toolchain defaults to the agent template: mise run lint-prose, mise run lint-messages, and the vale pre-commit hook all pass --output=ai-tells-agent.tmpl. Name the flag yourself only when invoking vale directly. The template prints one self-contained line per finding (location, severity, rule, the exact matched text, and the replacement parameter when the rule defines one) plus a totals line, so you can apply fixes without re-reading context through separate commands. Empty output means a clean run, and the exit code reports the result.

Read the full file on GitHub · 34 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 Changed · -2 tokens per session a6e2d12a3bb2
  2. 3d ago Changed · -1 tokens per session 89617c5fbae9
  3. 9d ago First seen · 34 lines · 970 tokens per session scan A 4488d7bcf307

Subscribe to this mod's changes

vale-ai-tells AGENTS.md is an instructions file published in the GitHub repository tbhb/vale-ai-tells (87 stars, last pushed today), licensed MIT. It adds 967 tokens to every session, about $0.0048 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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