seerai: Instructions file for Codex

AGENTS.md

seerai AGENTS.md is an instructions file for Codex, OpenCode from dralkh/seerai. It costs 13,692 tokens per session, scanned A, original, MIT.

Repository instructions for SeerAI, a Zotero plugin that adds AI chat, scholarly search, OCR, systematic review, storage, and structured research-data extraction. Zotero is an application for collecting and organizing research sources; the repository also contains a separate tool server and skills library.

In plain words
What is it for?
Use them when developing or building the Zotero plugin, MCP server, or agent skills, and when running formatting, linting, tests, releases, or extraction evaluations.
Why use it?
They explain the repository's separate plugin, server, and skill components, including that the plugin runs inside Zotero rather than Node.js.

Instructions file for CodexOpenCode

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

This is dralkh/seerai's own configuration. It tells Codex and OpenCode how to work on seerai 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 seerai configures →

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is import { config } from "../../package.json";.

Reuse

Borrowing it

Nothing to install: this file belongs to dralkh/seerai. 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/dralkh/seerai/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/dralkh/seerai

Made for: Codex, OpenCode.

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Per session 13,692 This file is loaded in full into every session.
When invoked 13,692 The same file — it is already loaded in full.
Security scan A 1 finding. 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 $0.13692 $0.13692
Opus 5.5 $0.05477 $0.05477
Sonnet 5.5 $0.02738 $0.02738
Haiku 4.5 $0.01369 $0.01369

Measured 18d ago against content hash 7560124e9933, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

seerai AGENTS.md scanned grade A with 1 finding 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 18d 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.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- **`workspace_bash` behavior differs**: In the plugin, it prompts the user to run the command manually. In the MCP server, it executes real shell commands via `node:child_process` in the workspace directory.
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

AGENTS.md · 695 lines

How it starts

The opening of the file, as written. The whole thing — 695 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Project Overview

seerai is an intelligent research assistant plugin for Zotero 8–10 that integrates AI-powered chat, federated scholarly search, RAG, OCR, systematic review, cloud storage, an agent skills library, and structured data extraction into the research workflow. The repo is a monorepo containing:

  • Zotero Plugin (src/, addon/) — runs inside Zotero's Firefox-based runtime (NOT Node.js)
  • MCP Server (mcp-server/) — standalone Node.js server exposing Zotero tools via Model Context Protocol
  • Agent Skills Library (skills/) — ~148 bundled, self-contained skill packages (SKILL.md + references/scripts) surfaced to agents via the skills tools

Commands

npm start              # Dev server with hot reload (zotero-plugin serve)
npm run build          # Production build: MCP bundle → plugin .xpi + tsc --noEmit + copies artifacts to root
npm run lint:check     # Prettier check + ESLint
npm run lint:fix       # Prettier write + ESLint fix
npm run release        # Create GitHub release (zotero-plugin release)
npm run test           # Run test suite (zotero-plugin test → mocha-based)
npm run test:extraction-eval  # LLM extraction evaluation harness (tsx test/extractionModelEval.ts)
npm run test:pipeline-eval    # Systematic-review pipeline evaluation harness (tsx test/pipelineEval.ts)
npm run test:rag-live         # Live RAG eval vs a real embedding provider (tsx test/ragLive.ts)
npm run update-deps    # Update all dependencies to latest (npm update --save)

# MCP server (separate package)
cd mcp-server && npm run dev      # Run MCP server with tsx
cd mcp-server && npm run bundle   # Bundle MCP server to dist/seerai-mcp.cjs
cd mcp-server && npm run build    # TypeScript compile (tsc)
cd mcp-server && npm run start    # Run compiled MCP server

Always run npm run lint:check and npm run build after making changes.

Live harness keys (.env, gitignored): test/ragLive.ts (npm run test:rag-live) reads EMBEDDING_BASE_URL (default https://nano-gpt.com/api/v1), EMBEDDING_API_KEY (or NANOGPT_API_KEY/LLM_API_KEY), EMBEDDING_MODEL (+ optional EMBEDDING_DIMENSIONS) to run the production embedding client + retrieval pipeline against a real provider with minimal Zotero stubs. Setting EMBEDDING_MODEL2 adds a second phase that switches models in the same data dir and asserts the embedding fingerprint invalidates and re-indexes every item on demand. Verified live against NanoGPT with text-embedding-3-small (1536 dims) and BAAI/bge-m3 (1024 dims). test/llmLive.ts / test/pipelineEval.ts read LLM_BASE_URL/LLM_API_KEY/LLM_MODEL/LLM_MODEL2. In the plugin itself, provider keys are entered in Preferences → seerai → AI providers and stored in {DataDirectory}/seerai/providerConfigs.json.

Read the full file on GitHub · 695 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. 18d ago Changed · +2 lines · +229 tokens per session 7560124e9933
  2. 1mo ago Changed · +25 lines · +1,567 tokens per session 9cff22db3153
  3. 1mo ago First seen · 668 lines · 11,896 tokens per session scan A fabed8aeb3b7

Subscribe to this mod's changes

seerai AGENTS.md is an instructions file published in the GitHub repository dralkh/seerai (94 stars, last pushed 18d ago), licensed MIT. It adds 13,692 tokens to every session, about $0.0548 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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