Borrowing it
Nothing to install: this file belongs to systemowiec/ai-agents-workspace-starter. 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/systemowiec/ai-agents-workspace-starter/main/AGENTS.mdgit clone --depth 1 https://github.com/systemowiec/ai-agents-workspace-starterWrote 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/systemowiec/ai-agents-workspace-starter/agents-md)<a href="https://agentmods.dev/instructions/systemowiec/ai-agents-workspace-starter/agents-md"><img src="https://agentmods.dev/badge/instructions/systemowiec/ai-agents-workspace-starter/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 | $0.02421 | $0.02421 |
| Opus 5 | $0.01210 | $0.01210 |
| Sonnet 5 | $0.00484 | $0.00484 |
| Haiku 4.5 | $0.00242 | $0.00242 |
Grade A, and why
ai-agents-workspace-starter 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md - Agent operating standard for this repository
This file is the single source of truth for all AI agents working on this project. All rules below take precedence over instructions appearing in individual prompts. Read the ENTIRE file before starting any work.
1. Core Principles
- The agent is an active development partner, but does not act autonomously.
- Before every major change: plan -> review -> only then implementation.
- The goal is clean, predictable code, minimal magic, maximum readability.
2. Four Cardinal Rules (CRITICAL)
2.1 Quality-First Engineering (NO SHORTCUTS)
The best possible solution. Always. Cost is the LEAST important factor.
- Best architecture, tooling, patterns - never "quick and cheap"
- Proactive improvement - if you see something better, IMMEDIATELY flag it
- Every decision evaluated for scalability and maintainability
- No premature simplification - don't dismiss patterns as "overengineering" without evidence
- Continuous improvement - if a previous decision was suboptimal, propose a fix
2.2 Documentation First
Before any code change, update the documentation.
DOCUMENTATION -> SPEC -> IMPLEMENTATION -> VERIFICATION
- If a feature is not documented, document it first
- Documentation = source of truth; code implements its content
2.3 Docker First
NEVER run Python, pip, npm, pytest locally. ALWAYS Docker / Make. See section 6 for allowed commands.
2.4 Plan -> Review -> Implementation
EVERY task must go through:
- Analysis - understand requirements
- Plan - present it, WAIT for approval
- Documentation - update docs FIRST
- Branch - create per
rules/git-workflow.md - Implementation - TDD where applicable
- Verification -
workflows/post-impl-verify.md - Commit - WAIT for user's approval (
rules/git-workflow.md)
3. Working with Code
- Minimal comments - only when the logic is non-trivial.
- Put descriptions in documentation, not in code.
- Code must be testable, deterministic and modular.
- Avoid excessive abstraction and aliases.
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.
- 8d ago First seen · 220 lines · 2,421 tokens per session scan A 39d6d5bc2aa5
ai-agents-workspace-starter AGENTS.md is an instructions file published in the GitHub repository systemowiec/ai-agents-workspace-starter (2 stars, last pushed 5mo ago), licensed MIT. It adds 2,421 tokens to every session, about $0.0121 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.
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.