ansari-skill AGENTS.md

ansari-skill AGENTS.md is an instructions file for Codex, OpenCode from ansari-project/ansari-skill. It costs 2,103 tokens per session, scanned A, original, MIT.

Repository instructions for ansari-skill, an AI-assisted development project using Codev protocols. They explain where agents find architecture guidance, lessons, protocols, templates, and project-specific rules.

In plain words
What is it for?
Use them when working on ansari-skill with Codev, selecting a development protocol, consulting architecture notes, or locating project resources and templates.
Why use it?
They give agents a consistent way to choose and follow workflows for planning, implementation, bug fixes, experiments, and reviews.

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/ansari-project/ansari-skill/agents-md
Clone the repo
git clone --depth 1 https://github.com/ansari-project/ansari-skill

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 ansari-skill AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/ansari-project/ansari-skill/agents-md.svg)](https://agentmods.dev/instructions/ansari-project/ansari-skill/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/ansari-project/ansari-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/ansari-project/ansari-skill/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 2,103 This file is loaded in full into every session.
When invoked 2,103 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 $0.02103 $0.02103
Opus 5 $0.01052 $0.01052
Sonnet 5 $0.00421 $0.00421
Haiku 4.5 $0.00210 $0.00210

Measured 4d ago against content hash df8e20ebe6dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ansari-skill 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 4d 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

2 near-identical copies found in the catalogue:

AGENTS.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ansari-skill - AI Agent Instructions

Always-On Engineering Context (hot tier)

Curated, always-on guidance — consult before deciding. Use each "consult when…" map to open the full arch.md / lessons-learned.md when relevant.

@codev/resources/arch-critical.md @codev/resources/lessons-critical.md

Note: This file follows the AGENTS.md standard for cross-tool compatibility with Cursor, GitHub Copilot, and other AI coding assistants. A Claude Code-specific version is maintained in CLAUDE.md.

Project Overview

This project uses Codev for AI-assisted development.

Available Protocols

  • SPIR: Multi-phase development with consultation (codev/protocols/spir/protocol.md)
  • ASPIR: Autonomous SPIR — no human gates on spec/plan (codev/protocols/aspir/protocol.md)
  • AIR: Autonomous Implement & Review for small features (codev/protocols/air/protocol.md)
  • BUGFIX: Bug fixes from GitHub issues (codev/protocols/bugfix/protocol.md)
  • PIR: Plan / Implement / Review — issue-driven with three human gates (plan-approval, dev-approval, pr) (codev/protocols/pir/protocol.md)
  • EXPERIMENT: Disciplined experimentation (codev/protocols/experiment/protocol.md)
  • MAINTAIN: Codebase maintenance (codev/protocols/maintain/protocol.md)
  • RESEARCH: Multi-agent research with 3-way investigation, synthesis, and critique (codev/protocols/research/protocol.md)

File Resolution (How Codev Finds Protocols and Templates)

Codev resolves protocol files, prompts, agent definitions, and roles through a four-tier lookup (highest priority first):

  1. .codev/<path> — user override (project-local customization)
  2. codev/<path> — project-local copy (customized and checked in)
  3. Runtime cache
  4. Installed package skeleton — ships with @cluesmith/codev (the default for every standard protocol)

Read the full file on GitHub · 163 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. 4d ago First seen · 163 lines · 2,103 tokens per session scan A df8e20ebe6dd

Subscribe to this mod's changes

ansari-skill AGENTS.md is an instructions file published in the GitHub repository ansari-project/ansari-skill (19 stars, last pushed 3d ago), licensed MIT. It adds 2,103 tokens to every session, about $0.0105 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.