unlazier-ai: Instructions file for Codex

AGENTS.md

unlazier-ai AGENTS.md is an instructions file for Codex, OpenCode from fco3lho/unlazier-ai. It costs 1,422 tokens per session, scanned A, original, MIT.

A set of general rules for an AI coding agent working on unlazier-ai. It emphasizes understanding the request, choosing a simple solution, and making small, deliberate changes.

In plain words
What is it for?
It helps plan coding tasks, surface trade-offs, review existing code, and implement narrowly scoped fixes or features.
Why use it?
It reduces assumptions, unnecessary complexity, and edits made before the task is understood. It also provides a way to ask focused questions when the requirements are unclear.

Instructions file for CodexOpenCode

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

This is fco3lho/unlazier-ai's own configuration. It tells Codex and OpenCode how to work on unlazier-ai 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 unlazier-ai configures →

Reuse

Borrowing it

Nothing to install: this file belongs to fco3lho/unlazier-ai. 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/fco3lho/unlazier-ai/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/fco3lho/unlazier-ai

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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Per session 1,422 This file is loaded in full into every session.
When invoked 1,422 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 $0.01422 $0.01422
Opus 5 $0.00711 $0.00711
Sonnet 5 $0.00284 $0.00284
Haiku 4.5 $0.00142 $0.00142

Measured 9d ago against content hash fb4d566e0b83, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

unlazier-ai 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 9d 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 · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Global Agent Rules

This document defines the mandatory standards for all code generation, refactoring, and documentation tasks. These rules exist to eliminate lazy coding, overengineering, silent assumptions, and incomplete work.

Tradeoff: These rules bias toward caution over speed. For trivial tasks (typo fixes, obvious one-liners), use judgment.


1. Think Before Coding

Don't assume. Don't hide confusion. Surface tradeoffs.

Before implementing:

  • State your assumptions explicitly. If uncertain, ask.
  • If multiple interpretations exist, present them — don't pick silently.
  • If a simpler approach exists, say so. Push back when warranted.
  • If something is unclear, stop. Name what's confusing. Ask.

When questioning the user, follow a structured approach:

  • Walk down each branch of the decision tree, resolving dependencies one by one.
  • Ask one question at a time. Wait for the answer before moving to the next.
  • For each question, provide your recommended answer alongside it.
  • If a question can be answered by exploring the codebase, explore instead of asking.

Example: User says "add export". Don't silently assume CSV. Ask: "Export to CSV, JSON, or both? All records or filtered?"

Example: User says "add a payment page." Ask: "Which payment provider? Stripe or something else? I recommend Stripe." Wait. Then: "Single payment or subscriptions?" And so on.


2. Simplicity First

Minimum code that solves the problem. Nothing speculative.

  • No features beyond what was asked.
  • No abstractions for single-use code.
  • No flexibility or configurability that wasn't requested.
  • No error handling for impossible scenarios.
  • If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

Good code solves today's problem simply, not tomorrow's problem prematurely.

Example: User asks for discount calculation. Don't build AbstractDiscountStrategy with factory pattern. Write calculate_discount(amount, percent).

Read the full file on GitHub · 161 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. 9d ago First seen · 161 lines · 1,422 tokens per session scan A fb4d566e0b83

Subscribe to this mod's changes

unlazier-ai AGENTS.md is an instructions file published in the GitHub repository fco3lho/unlazier-ai (3 stars, last pushed 3mo ago), licensed MIT. It adds 1,422 tokens to every session, about $0.0071 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.

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