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.
npx agentmods add rules/benchflow-ai/agents/projectgit clone --depth 1 https://github.com/benchflow-ai/agentsWhat 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 | $0.00175 | $0.00175 |
| Opus 5 | $0.00088 | $0.00088 |
| Sonnet 5 | $0.00035 | $0.00035 |
| Haiku 4.5 | $0.00017 | $0.00017 |
Grade A, and why
project 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.
This is a copy
100% identical to project — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
mini-SWE-agent overview
- mini-SWE-agent implements an AI software engineering agent that solves github issues and similar programming challenges
- The idea of this project is to write the simplest, smallest, most readable agent.
The project is structured as
minisweagent/__init__ # Protocols/interfaces for all base classes
minisweagent/agents # Agent control flow & loop
minisweagent/environments # Executing agent actions
minisweagent/models # LM interfaces
minisweagent/run # Run scripts that serve as an entry point
- The project embraces polymorphism: Every individual class should be simple, but we offer alternatives
- Every use case should start with a run script, that picks one agent, environment, and model class to run
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 · 22 lines · 175 tokens per session scan A fa161efe6593
project is a cursor rule published in the GitHub repository benchflow-ai/agents (10 stars, last pushed 2d ago), licensed Apache-2.0. It adds 175 tokens to every session, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to project, differing in 0 lines, and is treated as a copy.
Other cursor rules, from other repositories
engine-internals
Coding Agent engine implementation details (Cursor + Claude Code) — reference when modifying engine.ts or debugging Agent behavior.
testing-conventions
Testing conventions — must reference when modifying src/ code or tests.
architecture-constraints
GolemBot architecture hard constraints — must check before modifying any src/ code.
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
typescript
Changes to these high-fan-out internals can affect every message, delta, element, or rerun. Keep work in them minimal, and benchmark changes with representative stress-test apps.