katok AGENTS.md

Repository instructions for an AI coding agent working on Kakao Memory, a local macOS tool that indexes and searches KakaoTalk conversations. They describe the project's purpose, design rules, development practices, and privacy requirements.

In plain words
What is it for?
Use them when adding or changing KakaoTalk import, keyword or meaning-based search, archive storage, or the agent interface. They also guide tests with fake chat data and manual checks against a real installation.
Why use it?
They give the agent consistent project context and help prevent unsafe handling of private chat data. They also keep indexing, searching, and the command-line interface separated so changes are easier to manage.

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/nomadamas/katok/agents-md
Clone the repo
git clone --depth 1 https://github.com/NomaDamas/katok

Made for: Codex, OpenCode.

Per session 832 This file is loaded in full into every session.
When invoked 832 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 $0.00832 $0.00832
Opus 5 $0.00416 $0.00416
Sonnet 5 $0.00166 $0.00166
Haiku 4.5 $0.00083 $0.00083

Measured 2d ago against content hash 5f83c8b4d014, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

katok 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 2d 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 · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Kakao Memory Agent Instructions

These instructions apply to this repository and all child directories.

Project Intent

Kakao Memory is a local-first semantic memory and search layer for KakaoTalk conversations on macOS. Treat it as privacy-sensitive infrastructure, not a casual chat analyzer.

Architecture Guidelines

  • Prefer source adapters over duplicating DB reverse engineering logic.
  • The first source adapter should integrate with kakaocli or the k-skill kakaotalk-mac helper.
  • Keep ingestion, normalized archive, keyword search, semantic search, and skill wrapper as separable modules.
  • Use stable message identifiers and incremental cursors so indexing can resume without rereading everything.
  • Keep the agent skill thin: it should call the CLI and summarize results, not own indexing logic.

Development Guidelines

  • Add tests before behavior changes.
  • Use fixtures with synthetic chat data only.
  • Do not create tests that depend on the user's real KakaoTalk installation or real local DB.
  • Real KakaoTalk smoke tests may be manual-only and must avoid printing private content.
  • Nothing derived from a real archive may be committed, including in documentation. This repository is public; the archive it reads is not. Avoiding private content in session output is not enough, because a finding made while looking at live data tends to get written down next to the rule it justified — a quoted message, a room name, a person's name or kinship term, a sample used because it was at hand. Skill files, comments, tests, and changelogs are all published. State the rule and drop the evidence: the observation that convinced you is for this conversation, not for the commit. Fixtures stay synthetic even when a real value would have been easier to paste.
  • Keep README, CLI help, and privacy behavior aligned in the same change.
  • Verify against the toolchain CI pins, and run every gate CI runs. .github/workflows/ci.yml pins the Rust version (matching rust-version in Cargo.toml) and runs five gates: cargo fmt --all -- --check, cargo clippy --all-targets -- -D warnings, cargo test --all-targets, cargo publish --dry-run, and scripts/verify_release_config.py. A newer local toolchain passes work that CI rejects, because clippy retires and re-scopes lints between releases — so cargo +<pinned> clippy is the check that counts. Running a subset and reporting it as green is the failure mode this exists to prevent.

Read the full file on GitHub · 65 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. 2d ago First seen · 65 lines · 832 tokens per session scan A 5f83c8b4d014

Subscribe to this mod's changes

katok AGENTS.md is an instructions file published in the GitHub repository NomaDamas/katok (262 stars, last pushed 20d ago), licensed MIT. It adds 832 tokens to every session, about $0.0042 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.

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