codex-lean-team: Instructions file for Codex

AGENTS.md

codex-lean-team AGENTS.md is an instructions file for Codex, OpenCode from gabriele-mastrapasqua/codex-lean-team. It costs 986 tokens per session, scanned A, original, MIT.

A set of instructions for a coding agent called Luna, covering how it executes tasks, chooses models, and delegates focused work.

In plain words
What is it for?
It is for guiding code implementation, architecture decisions, debugging, unfamiliar code paths, and validation.
Why use it?
It gives the agent a consistent way to decide when to work directly and when to ask a specialist for help.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions subagents.

This is gabriele-mastrapasqua/codex-lean-team's own configuration. It tells Codex and OpenCode how to work on codex-lean-team 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 codex-lean-team configures →

Reuse

Borrowing it

Nothing to install: this file belongs to gabriele-mastrapasqua/codex-lean-team. 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/gabriele-mastrapasqua/codex-lean-team/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/gabriele-mastrapasqua/codex-lean-team

Made for: Codex, OpenCode.

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Per session 986 This file is loaded in full into every session.
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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 $0.00986 $0.00986
Opus 5 $0.00493 $0.00493
Sonnet 5 $0.00197 $0.00197
Haiku 4.5 $0.00099 $0.00099

Measured 7d ago against content hash d585ae13b6a4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

codex-lean-team 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 7d 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 · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Lean Team v2: execution-first engineering

Model hierarchy

  • Luna (root): fastest, cheapest, for all direct implementation. Reasoning effort: high.
  • Luna (specialist): same economical model for focused work. Reasoning effort: high by default, max for debugger and native/unsafe code.

Default execution policy

The root agent (Luna) implements tasks directly by default, but may delegate a narrow sub-question to a specialist when it would save time or reduce risk. Most tasks are completed by the main agent alone; a task with concrete uncertainty or a specialist domain should use one focused, read-only specialist early. The root keeps ownership of edits and validation.

Routing

  • Clear or ordinary task → Luna implements directly.
  • Cross-module but clear → Luna implements directly.
  • Ambiguous architecture → Luna inspects → delegate to Luna planner for competing designs or rollback/compatibility tradeoffs → Luna implements.
  • Difficult bug → Luna reproduces or inspects → delegate to Luna debugger at max for cross-layer, intermittent, previously failed, or multi-hypothesis bugs → Luna fixes.
  • Unfamiliar or cross-cutting path → Luna delegates one narrow question to Luna explorer as an early scout when it can quickly remove uncertainty.
  • Native or unsafe code → delegate to Luna native at max for C/C++, Rust, SIMD, CUDA/Metal, memory ownership, atomics, or FFI boundaries.
  • High-risk implementation → Luna implements → delegate to Luna reviewer before completion.
  • Performance with benchmark → delegate to Luna performance specialist.
  • AI/ML, infrastructure, deployment, CI/CD, cloud, containers → delegate to the matching Luna specialist at high when the task is materially in that domain.

"Cross-module" is not a trigger. Multi-file changes are normal development.

Delegation guidelines

Delegate when a specialist can answer a concrete question, reduce uncertainty, or cover a domain the root agent is not confident in. A full blocker is not required: use one focused specialist early when its output is likely to change the next implementation step.

Read the full file on GitHub · 108 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. 7d ago First seen · 108 lines · 986 tokens per session scan A d585ae13b6a4

Subscribe to this mod's changes

codex-lean-team AGENTS.md is an instructions file published in the GitHub repository gabriele-mastrapasqua/codex-lean-team (3 stars, last pushed 1mo ago), licensed MIT. It adds 986 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.

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