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privacy-kit-cl: Instructions file for Codex

AGENTS.md

privacy-kit-cl AGENTS.md is an instructions file for Codex, OpenCode from Yugoxc/privacy-kit-cl. It costs 869 tokens per session, scanned A, original, MIT.

Integration instructions for adding privacy-kit-cl to an application so it handles personal data according to Chilean Law 21.719.

In plain words
What is it for?
Use them when integrating the kit into Python or Node.js systems such as APIs, bots, or workers, including data sent to language models, payment services, external APIs, and logs.
Why use it?
They help an agent find where personal data enters, leaves, and is stored, then connect those points to the privacy kit without rewriting the business logic.

Instructions file for CodexOpenCode

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

This is Yugoxc/privacy-kit-cl's own configuration. It tells Codex and OpenCode how to work on privacy-kit-cl 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 privacy-kit-cl configures →

not rated 11repo 4mo ago A scan 869 tokens original MIT
View source ↗ Yugoxc/privacy-kit-cl npmjs.com
Reuse

Borrowing it

Nothing to install: this file belongs to Yugoxc/privacy-kit-cl. 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/Yugoxc/privacy-kit-cl/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Yugoxc/privacy-kit-cl

Made for: Codex, OpenCode.

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README.md
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Per session 869 This file is loaded in full into every session.
When invoked 869 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 $0.00869 $0.00869
Opus 5.5 $0.00348 $0.00348
Sonnet 5.5 $0.00174 $0.00174
Haiku 4.5 $0.00087 $0.00087

Measured 2mo ago against content hash 135d926a3f76, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

privacy-kit-cl 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 2mo 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 · 43 lines

How it starts

The opening of the file, as written. The whole thing — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Guía de integración para una IA

Este archivo le indica a un agente de IA cómo acoplar privacy-kit-cl a un sistema (nuevo o existente) para cumplir la Ley 21.719. Seguir los pasos en orden.

Objetivo

Envolver todos los puntos donde el sistema recibe, procesa, almacena o transfiere datos personales con los componentes del kit, sin reescribir la lógica de negocio.

Paso 0 — Detectar el terreno

  1. Identifica el lenguaje/stack y el punto de entrada (API, bot, worker).
  2. Localiza dónde entran datos personales: RUT, nombre, teléfono, email, dirección, ubicación, medios de pago, historial.
  3. Localiza dónde SALEN a terceros: llamadas a LLMs (OpenAI/Anthropic), pasarelas de pago, APIs externas, logs.

Paso 1 — Instalar y configurar

  1. Instala el paquete del lenguaje del sistema:
    • Python: pip install "git+https://github.com/Yugoxc/privacy-kit-cl.git" (código en python/privacy_kit/).
    • Node.js: npm install github:Yugoxc/privacy-kit-cl (código en node/src/).
  2. Crea el archivo de configuración a partir de DEFAULT_CONFIG (python/privacy_kit/config.py o node/src/config.js). Rellena:
    • data_categories: qué datos personales trata este sistema.
    • purposes: finalidades (ej. "asistencia_venta", "despacho").
    • retention_days: plazo por categoría.
    • third_parties: terceros a los que se envían datos (nombre, país, base legal).
    • legal_basis: base de licitud por finalidad (consentimiento | interés_legítimo | contrato).

Paso 2 — Implementar el Store

Elige el adaptador de almacenamiento: implementa la interfaz PrivacyStore (python/privacy_kit/store/base.py o node/src/store/base.js) sobre la BD existente del sistema (Mongo, ClickHouse, Postgres). Solo 6 métodos. Si no hay BD, usa InMemoryStore para prototipar.

Paso 3 — Envolver los 5 puntos de control (en este orden de prioridad)

  1. Minimización antes de LLM/terceros — CRÍTICO: envuelve TODA llamada a un LLM/API externa con pk.redaction.redact(texto, subject_id) para quitar PII. Registra la transferencia con pk.transfers.log(...).
  2. Aviso + base de licitud — en el primer contacto con el titular, entrega el aviso (pk.notice.render()) y registra la base (pk.consent.capture(...) si aplica consentimiento).
  3. Auditoría — en cada acceso a un dato personal, llama pk.audit.record(...).
  4. Derechos ARCOP — expón los handlers de pk.rights (acceso/rectificación/borrado/oposición/portabilidad) como endpoints o intents del bot.
  5. Retención — agenda pk.retention.sweep() (cron/worker) para borrar datos vencidos.

Read the full file on GitHub · 43 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. 2mo ago First seen · 43 lines · 869 tokens per session scan A 135d926a3f76

Subscribe to this mod's changes

privacy-kit-cl AGENTS.md is an instructions file published in the GitHub repository Yugoxc/privacy-kit-cl (11 stars, last pushed 4mo ago), licensed MIT. It adds 869 tokens to every session, about $0.0035 per session on Opus 5.5. 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.

Backend and APIsLegal and complianceaianonymizationchilecompliancedata-privacydata-protection
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deepseek-harness AGENTS.mddeepseek-ai/deepseek-harnessInstructions file274k2d agoMITA4,313Codex, OpenCode