RAGLight: Instructions file for Codex

AGENTS.md

RAGLight AGENTS.md is an instructions file for Codex, OpenCode from Bessouat40/RAGLight. It costs 1,252 tokens per session, scanned A, original, MIT.

A repository guide for contributors and coding agents working on RAGLight, a Python library for retrieval-augmented generation (RAG), which combines searched information with an AI response. It explains the project structure, engineering rules, public API, integrations, and testing workflow.

In plain words
What is it for?
Use it to understand where changes belong, follow dependency and API rules, add or update integrations, migrate older code, and validate changes with the project’s tests.
Why use it?
It gives people and coding agents one authoritative place to check before changing the code. This reduces rule duplication, incompatible edits, and missed test requirements; TDD means writing tests before or alongside the code.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is Bessouat40/RAGLight's own configuration. It tells Codex and OpenCode how to work on RAGLight 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 RAGLight configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Bessouat40/RAGLight. 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/Bessouat40/RAGLight/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/Bessouat40/RAGLight

Made for: Codex, OpenCode.

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Per session 1,252 This file is loaded in full into every session.
When invoked 1,252 The same file — it is already loaded in full.
Security scan A 0 findings. 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 $0.01252 $0.01252
Opus 5.5 $0.00501 $0.00501
Sonnet 5.5 $0.00250 $0.00250
Haiku 4.5 $0.00125 $0.00125

Measured 13d ago against content hash ff786b19741d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

RAGLight 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 13d 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 · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

RAGLight contributor and agent guide

This file is the authoritative starting point for humans and AI coding agents working in this repository. Tool-specific instruction files must link here and must not duplicate these rules.

RAGLight is a Python library for building retrieval-augmented generation pipelines. Version 4 keeps the core small, makes integrations optional, and exposes stable extension contracts. The v3 CLI, HTTP server, UI, and agentic runtime are not compatibility layers in the v4 tree.

Start here

Read the documents relevant to the change before editing code:

Document Purpose
docs/architecture.md Current v4 layers and dependency rules
docs/development.md Environment setup and validation commands
docs/dependencies.md Optional extras, dependency ownership, and package audit
docs/testing.md TDD workflow and test pyramid
docs/integrations.md Checklist for adding or changing a provider
docs/public-api.md Public API policy and compatibility expectations
docs/migration-v3-to-v4.md Authoritative migration map from legacy APIs
docs/error-handling.md Error ownership and actionable failures
docs/releasing.md Package and release validation
docs/decisions/ Architecture decision records

Documentation must distinguish implemented v4 behavior from capabilities that are explicitly planned for a later issue.

Repository map

src/raglight/
  contracts/             stable structural extension protocols
  models/                provider-independent data models
  pipeline/              classic RAG orchestration
  integrations/          optional provider adapters
tests/                    existing unit and component tests
tests/architecture/       executable dependency guardrails
tests/integration/        cross-component tests
tests/e2e/                public workflow tests

Do not restore removed v3 packages as compatibility shims. New optional capabilities must be designed on the boundaries in docs/architecture.md.

Read the full file on GitHub · 154 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. 13d ago First seen · 154 lines · 1,252 tokens per session scan A ff786b19741d

Subscribe to this mod's changes

RAGLight AGENTS.md is an instructions file published in the GitHub repository Bessouat40/RAGLight (673 stars, last pushed 13d ago), licensed MIT. It adds 1,252 tokens to every session, about $0.0050 per session on Opus 5.5. 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 2026-10-16.

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