Borrowing it
Nothing to install: this file belongs to Insight-Services-APAC/ingenious. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Insight-Services-APAC/ingenious/main/AGENTS.mdgit clone --depth 1 https://github.com/Insight-Services-APAC/ingeniousWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/insight-services-apac/ingenious/agents-md)<a href="https://agentmods.dev/instructions/insight-services-apac/ingenious/agents-md"><img src="https://agentmods.dev/badge/instructions/insight-services-apac/ingenious/agents-md.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01331 | $0.01331 |
| Opus 5 | $0.00665 | $0.00665 |
| Sonnet 5 | $0.00266 | $0.00266 |
| Haiku 4.5 | $0.00133 | $0.00133 |
Grade A, and why
ingenious 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
This file provides guidance to coding agents when working with code in this repository.
Important Note on Your Context Window
Your context window will be automatically compacted as it approaches its limit, allowing you to continue working indefinitely from where you left off. Therefore, do not stop tasks early due to token budget concerns. As you approach your token budget limit, save your current progress and state to memory before the context window refreshes. Always be as persistent and autonomous as possible and complete tasks fully, even if the end of your budget is approaching. Never artificially stop any task early regardless of the context remaining.
Repository Context
This is the ingenious package - a core AI agent framework library (v0.2.8).
Communication Style
CRITICAL: When working with this codebase:
- NEVER use emojis in any communication, code, comments, or documentation
- Always maintain a concise, professional tone in all interactions
- Provide direct, clear technical communication without unnecessary elaboration
- Focus on facts and technical accuracy over conversational language
Testing and Development Files
CRITICAL: All testing artifacts, temporary files, and development scripts must be placed in the /tmp folder to maintain repository cleanliness:
- Development scripts and experiments
- Temporary output files
- Test artifacts and logs
- Mock data generators
This prevents clutter in the working directory and ensures consistent cleanup across development environments.
Package Management
Uses uv for Python package and environment management. Python 3.13+ is required.
High-Level Architecture
Core Components
- FastAPI Server (
ingenious/main/app_factory.py) - Main API application factory using dependency injection - Multi-Agent System (
ingenious/services/chat_services/multi_agent/) - AutoGen-based agent orchestration - Conversation Flows (
services/chat_services/multi_agent/conversation_flows/) - Pluggable workflow patterns - Dependency Injection (
ingenious/services/fastapi_dependencies.py) - FastAPI-native dependency wiring - Configuration - Pydantic-settings based (
ingenious/config/) withINGENIOUS_*environment variables
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.
- yesterday First seen · 128 lines · 1,331 tokens per session scan A 1d6118398558
ingenious AGENTS.md is an instructions file published in the GitHub repository Insight-Services-APAC/ingenious (24 stars, last pushed 7mo ago), licensed MIT. It adds 1,331 tokens to every session, about $0.0067 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 2026-09-04.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.