kaora-memory AGENTS.md

kaora-memory AGENTS.md is an instructions file for Codex, OpenCode from alex-lamport/kaora-memory. It costs 3,857 tokens per session, scanned A, original, MIT.

An AGENTS.md instruction file describing the identity, technology, development stage, and communication rules of the kaora-memory project. AGENTS.md is a project guide that coding agents can load automatically.

In plain words
What is it for?
Use it to tell agents about the Python package, command-line interface, tests, PyPI release process, project decisions, and preferred communication style.
Why use it?
It gives agents shared project context and operating rules so their changes and conversations follow the repository's intended setup.

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/alex-lamport/kaora-memory/agents-md
Clone the repo
git clone --depth 1 https://github.com/alex-lamport/kaora-memory

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 kaora-memory AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/alex-lamport/kaora-memory/agents-md.svg)](https://agentmods.dev/instructions/alex-lamport/kaora-memory/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/alex-lamport/kaora-memory/agents-md"><img src="https://agentmods.dev/badge/instructions/alex-lamport/kaora-memory/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 3,857 This file is loaded in full into every session.
When invoked 3,857 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 5.1 $0.03857 $0.03857
Opus 5 $0.01929 $0.01929
Sonnet 5 $0.00771 $0.00771
Haiku 4.5 $0.00386 $0.00386

Measured 5d ago against content hash 0a8c69a9455f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

kaora-memory 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 5d 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 · 245 lines

How it starts

The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — kaora-memory

Canonical operating-memory file. Auto-loaded by Codex CLI · Cursor · Aider · Gemini CLI · OpenAI Agents. Claude Code loads it through an import in CLAUDE.md (line @AGENTS.md). Update when identity, stack, stage, or architectural decisions change.


1. Project identity

Name: kaora-memory Pitch: Open-source skill for persistent memory and codified behavior for AI agents (Claude Code, Codex, Cursor, Gemini CLI). Owner: Alexis Rojas · X @alex_lamports · GitHub @alex-lamport Path: ~/Desktop/kaora-memory Year: 2026 Current stage: v0.1 shipped · 0.1.2 live on PyPI · launch communication in progress (Block 5, second half)

2. Tech stack

Layer Technology
Package Python >=3.10 · build backend hatchling
Layout flat — kaora_memory/ alongside pyproject.toml (NO src/)
CLI click >= 8.1.0
Entry point kaora = kaora_memory.cli:main
Tests pytest (in [project.optional-dependencies].dev)
Distribution PyPI (pip install kaora-memorykaora init)

3. Communication register

  • Language: Italian for live conversation with the user. English for docs, logs, code, comments, and any written artifact on disk.
  • Tone: direct, concise, no preambles, no "great", no "I'd love to", no redundant alternatives unless asked.
  • One direction at a time. Never 4 options in a batch. One proposal, confirmation, go.
  • One question at a time. Never bundle 3 questions into one.
  • Decider vs Executor: Alexis Rojas decides, the agent executes. Advise only if asked.

Conversational mode — Operative vs Learning

The agent recognizes at every moment which of the two modes the user is in and adapts accordingly.

Operative

  • Signals: direct imperatives ("go", "do it", "proceed", "write", "implement"), confirmation of a prior proposal ("yes", "ok", "ok go").
  • Behavior: propose a concrete action in 1-2 lines, wait for "go", execute.

Read the full file on GitHub · 245 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. 5d ago First seen · 245 lines · 3,857 tokens per session scan A 0a8c69a9455f

Subscribe to this mod's changes

kaora-memory AGENTS.md is an instructions file published in the GitHub repository alex-lamport/kaora-memory (1 stars, last pushed 3mo ago), licensed MIT. It adds 3,857 tokens to every session, about $0.0193 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