mcp-walmart-ads: Instructions file for Codex

AGENTS.md

mcp-walmart-ads AGENTS.md is an instructions file for Codex, OpenCode from alyiox/mcp-walmart-ads. It costs 989 tokens per session, scanned A, original, MIT.

A repository instruction file for the Walmart Ads MCP project, a tool that connects agents to Walmart advertising services. It defines commit-message and release-tag rules.

In plain words
What is it for?
It is for guiding agents when writing commits, following code style, and creating annotated version tags for releases.
Why use it?
It keeps changes and releases consistent with the project's conventions and avoids shell problems when creating commits.

Instructions file for CodexOpenCode

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

This is alyiox/mcp-walmart-ads's own configuration. It tells Codex and OpenCode how to work on mcp-walmart-ads 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 mcp-walmart-ads configures →

Reuse

Borrowing it

Nothing to install: this file belongs to alyiox/mcp-walmart-ads. 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/alyiox/mcp-walmart-ads/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/alyiox/mcp-walmart-ads

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 mcp-walmart-ads AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/alyiox/mcp-walmart-ads/agents-md.svg)](https://agentmods.dev/instructions/alyiox/mcp-walmart-ads/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/alyiox/mcp-walmart-ads/agents-md"><img src="https://agentmods.dev/badge/instructions/alyiox/mcp-walmart-ads/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 989 This file is loaded in full into every session.
When invoked 989 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 $0.00989 $0.00989
Opus 5 $0.00495 $0.00495
Sonnet 5 $0.00198 $0.00198
Haiku 4.5 $0.00099 $0.00099

Measured 6d ago against content hash 95227c000f1a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

mcp-walmart-ads 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 6d 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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

AGENTS.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Instructions

Rules AI agents must follow when working in this repository.


Commit messages

Use Conventional Commits.

Header

  • Format: <type>(optional scope): summary
  • Use lowercase types (feat, fix, ci, chore, docs)
  • Use scopes when relevant
  • Write summaries in lowercase, imperative mood

Body

  • Leave a blank line after the header
  • Explain why, not what
  • Use imperative, present tense
  • Wrap lines at ~72 characters

The body is optional for trivial changes.


Release tags

  • Use the bare version as the tag name — no v prefix (e.g. 0.1.0a4, not `v0.1.0a4``)
  • Tags must be annotated (git tag -a) with a structured release-notes message

Commits

When generating commits via a shell:

  • Do not pass generated messages directly to git commit -m
  • Write the commit message to a file or standard input
  • Use git commit -F <file> or git commit -F -
  • Disable shell expansion when writing commit messages

This avoids issues with backticks, quotes, and other shell-expanded characters in generated commit messages.


Code style

Follow existing project conventions.

  • Match formatting, naming, and file structure already in use
  • Do not reformat unrelated code
  • Prefer small, focused changes
  • Avoid introducing new patterns without clear benefit

Language-specific rules

  • Respect .editorconfig when present
  • Do not disable lint rules without justification
  • Prefer explicit, readable code over clever abstractions
  • Ensure all changes pass ruff check ., ruff format --check ., pyright, and pytest

uv Workflow Rules

  • Use uv exclusively for dependency management instead of pip
  • Always prefix tool and script invocations with uv run so they execute inside the managed environment
  • Do not manually create, activate, or delete .venv directories
  • Use uv version <new-version> to bump the project version — do not edit pyproject.toml directly
  • Always commit both pyproject.toml and uv.lock together after a version bump

Read the full file on GitHub · 114 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. 6d ago First seen · 114 lines · 989 tokens per session scan A 95227c000f1a

Subscribe to this mod's changes

mcp-walmart-ads AGENTS.md is an instructions file published in the GitHub repository alyiox/mcp-walmart-ads (1 stars, last pushed 19d ago), licensed MIT. It adds 989 tokens to every session, about $0.0049 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 2026-08-31.

Related

Other instructions, from other repositories

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens