srchd AGENTS.md

Project instructions documenting the architecture, requirements, commands, database, and main components of the `srchd` application.

In plain words
What is it for?
Use it when working on `srchd`, including its AI-agent publication and review workflow, SQLite database, migrations, type checks, and linting.
Why use it?
It gives coding agents the project context and the approved commands they need to make changes without guessing how the system is organised.

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/dust-tt/srchd/agents-md
Clone the repo
git clone --depth 1 https://github.com/dust-tt/srchd

Made for: Codex, OpenCode.

Per session 1,130 This file is loaded in full into every session.
When invoked 1,130 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 $0.01130 $0.01130
Opus 5 $0.00565 $0.00565
Sonnet 5 $0.00226 $0.00226
Haiku 4.5 $0.00113 $0.00113

Measured 3d ago against content hash 2c5507fbfe06, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

srchd 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 3d 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 · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md - Architecture Documentation

Requirements

  • Node.js: v24.15+ required
    • On macOS with Homebrew: export PATH="/opt/homebrew/opt/node@24/bin:$PATH"

Commands

  • Run CLI: npx tsx src/srchd.ts
  • Type checking: npm run typecheck
  • Linting: npm run lint
  • Database migrations: npx drizzle-kit generate && npx drizzle-kit migrate

Architecture Overview

srchd orchestrates AI agents through a publication/review system. Agents collaborate to solve complex problems by publishing papers, reviewing each other's work, and citing relevant publications.

Core Components

Database Layer (src/db/)

ORM: Drizzle ORM with SQLite backend (./db.sqlite)

Schema Entities:

  • experiments - Experiment metadata with unique names and problem statements
  • agents - AI agents with model, provider, thinking config, and tools
  • evolutions - System prompt evolution history for self-improvement
  • messages - Agent conversation history with position tracking
  • publications - Research papers with status (SUBMITTED/PUBLISHED/REJECTED)
  • citations - Citation relationships between publications
  • reviews - Peer reviews with grades (STRONG_ACCEPT/ACCEPT/REJECT/STRONG_REJECT)
  • solutions - Tracked solutions with reasoning and publication references
  • token_usages - Token usage tracking for cost monitoring

Key Data Relationships:

  • Experiments contain multiple agents
  • Agents have memories and can author publications
  • Publications can cite other publications within experiments
  • Publications undergo peer review by agents
  • All entities maintain created/updated timestamps

CLI Interface (src/srchd.ts)

Built with Commander.js, provides commands for:

  • Experiment management (create, list, metrics)
  • Agent management (create, list, evolve, run)
  • Computer image building
  • Web UI server

Agent Profile System (src/agent_profile.ts)

Profiles define pre-configured agent types in agents/<profile-name>/:

  • prompt.md - System prompt defining behavior and objectives
  • settings.json - Tools, environment variables, Docker image name
  • Dockerfile (optional) - Custom Docker environment for computer-use agents

Read the full file on GitHub · 134 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. 3d ago First seen · 134 lines · 1,130 tokens per session scan A 2c5507fbfe06

Subscribe to this mod's changes

srchd AGENTS.md is an instructions file published in the GitHub repository dust-tt/srchd (91 stars, last pushed 12d ago), licensed MIT. It adds 1,130 tokens to every session, about $0.0056 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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