argus AGENTS.md

Repository instructions for AI coding agents working on Argus, a search system that routes requests across multiple search and answer providers. It describes the project’s features, deployment tiers, provider routing, and contribution-related files.

In plain words
What is it for?
It is for guiding work on search providers, routing, content extraction, database-backed sessions, deployment options, and related project documentation.
Why use it?
It gives agents the project context and operating rules needed to make changes consistently in the repository.

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/khamel83/argus/agents-md
Clone the repo
git clone --depth 1 https://github.com/Khamel83/argus

Made for: Codex, OpenCode.

Per session 3,021 This file is loaded in full into every session.
When invoked 3,021 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 $0.03021 $0.03021
Opus 5 $0.01510 $0.01510
Sonnet 5 $0.00604 $0.00604
Haiku 4.5 $0.00302 $0.00302

Measured 2d ago against content hash 6f197f54aa7d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

argus 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 · 240 lines

How it starts

The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Argus

What this file is for: the canonical guide for AI coding agents working in this repository (Claude Code, Codex, Cursor, Copilot, OpenCode, and friends). Human contributors should start with CONTRIBUTING.md; background on the project lives in CONTEXT.md and README.md. CLAUDE.md is a short pointer back here with Claude-Code-specific notes.

Overview

Search infrastructure for AI agents: 14 providers, topology-aware routing, WolframAlpha computed answers, and a 12-step content extraction chain. Provider adapters: SearXNG (self-hosted, aggregates 70+ engines, disabled by default), DuckDuckGo, Yahoo (scraped), GitHub, WolframAlpha (free API, computed answers), Brave, Tavily, Exa, Linkup, Parallel AI (monthly credit for eligible accounts with a card on file), Serper, You.com, Valyu, SearchAPI. Tier-based routing: free providers first, monthly recurring next, one-time credits last. Budget enforcement skips exhausted providers automatically. Multi-turn sessions use the configured SQL repository.

Features

  • Topology-aware acquisition — Argus knows if it's on a residential IP or datacenter, routing search and extraction automatically to avoid blocks and minimize network hops.
  • Adaptive Domain Memory — Learns which domains fail from datacenter IPs but succeed from residential ones, automatically routing future requests for those domains to residential egress.
  • Universal Provenance — Every search result and extraction is tagged with egress (residential|datacenter), machine, and source_type.
  • Intelligent Routing — Tier-based routing: free providers first, monthly recurring next, one-time credits last. Budget enforcement skips exhausted providers automatically.
  • 12-step Extraction — Trafilatura → Crawl4AI → Playwright → Jina → Valyu → Firecrawl → You → Archive with quality gates and completeness assessment.

Two Deployment Tiers

Tier 1: No server (API keys only)

  • pip install argus-search — works immediately with DuckDuckGo + Yahoo
  • Add WOLFRAM_APP_ID for computed answers (math, facts, conversions — 2,000 free/month)
  • Add API keys for 7,000+ more free monthly queries; eligible Parallel accounts with a card on file can bring the total to as much as 12,000+
  • Extraction via external APIs only (Jina, Valyu Contents, Firecrawl, You.com Contents, Wayback)
  • Default SQLite persistence (no database server required)
  • Works on any machine with Python 3.11+ (laptop, Mac Mini, Pi, cloud VM)

Read the full file on GitHub · 240 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 · 240 lines · 3,021 tokens per session scan A 6f197f54aa7d

Subscribe to this mod's changes

argus AGENTS.md is an instructions file published in the GitHub repository Khamel83/argus (4 stars, last pushed 2d ago), licensed MIT. It adds 3,021 tokens to every session, about $0.0151 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 2026-08-31.