memex AGENTS.md

Repository-specific instructions for AI agents working on Memex, a service accessed through the Model Context Protocol. They describe the required workflow for changes, testing, deployment, and self-review.

In plain words
What is it for?
Use them when changing Memex code, documentation, infrastructure, or deployment configuration.
Why use it?
They prevent agents from skipping project rules such as reading the required documentation, using tests where appropriate, and confirming risky operations.

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/timurgaleev/memex/agents-md
Clone the repo
git clone --depth 1 https://github.com/timurgaleev/memex

Made for: Codex, OpenCode.

Per session 2,313 This file is loaded in full into every session.
When invoked 2,313 The same file — it is already loaded in full.
Security scan B 2 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 $0.02313 $0.02313
Opus 5 $0.01156 $0.01156
Sonnet 5 $0.00463 $0.00463
Haiku 4.5 $0.00231 $0.00231

Measured 2d ago against content hash eb6c245176b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

memex AGENTS.md scanned grade B with 2 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

| wget -qO- --post-file=/dev/stdin --header=Content-Type:application/json http://127.0.0.1:18790/mcp

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

| wget -qO- --post-file=/dev/stdin --header=Content-Type:application/json http://127.0.0.1:18790/mcp
AGENTS.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Working in this Repo as an AI Agent

Companion to llms.txt (which is the doc map). This file is how to work: build, test, deploy, commit. Read CLAUDE.md first — it carries the user's irrevocable rules.

TL;DR

  • Always confirm before destructive ops (commit, terraform apply, EC2 recreate).
  • TDD where the logic is testable; smoke-test where the network is the test.
  • Containers run on a single EC2; deploy = git pull && docker compose up -d --build over SSM.
  • memex's brain index is rebuildable from source content; if RDS is wiped, re-sweep restores it (~5-10 min, $0 — Titan is credit-eligible).
  • memex is reached over MCP only (POST /mcp, through cloudflared or — with ingress_mode = "caddy" — a Caddy sidecar on the instance's own IP). No chat surface, no bot — just MCP clients (Claude Code, Cursor, …).

Required workflow — run the skill for every change

No change is "done" until the skills have run. For every change — features, fixes, refactors, docs, infra — in order:

  1. Self-review skill/agent. Dispatch the review agent whose specialty matches what you changed (the table in CLAUDE.md → "Self-review after each implementation"): security-engineer for auth / secrets / ingress, code-reviewer for logic / refactor, quality-guard for new tests, devops-automator for CI / docker / terraform, ai-engineer for engine / MCP / retrieval, reality-checker for "it's live now" claims, bug-hunter for adversarial sweeps, technical-writer for docs. Act on every CRITICAL / HIGH finding before declaring done.
  2. Ship workflow. Follow CLAUDE.md → "Ship workflow": test → push → deploy → verify → release, in that order, every time. A change is not shipped until the live EC2 is running it and /health + the MCP smoke-test pass; user-facing version bumps end with a SemVer tag + GitHub release (see "Release" below).

Both are non-negotiable and apply even to one-line fixes — the cost of one extra skill/agent run is cheaper than a production regression.

Read the full file on GitHub · 173 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 · 173 lines · 2,313 tokens per session scan B eb6c245176b9

Subscribe to this mod's changes

memex AGENTS.md is an instructions file published in the GitHub repository timurgaleev/memex (8 stars, last pushed 7d ago), licensed MIT. It adds 2,313 tokens to every session, about $0.0116 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.