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/linhai0872/agno-agent-starter/globalgit clone --depth 1 https://github.com/linhai0872/agno-agent-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/rules/linhai0872/agno-agent-starter/global)<a href="https://agentmods.dev/rules/linhai0872/agno-agent-starter/global"><img src="https://agentmods.dev/badge/rules/linhai0872/agno-agent-starter/global.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 | $0.00000 | $0.00577 |
| Opus 5 | $0.00000 | $0.00289 |
| Sonnet 5 | $0.00000 | $0.00115 |
| Haiku 4.5 | $0.00000 | $0.00058 |
Grade A, and why
global 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 4d 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.
What it actually says
Agno Agent Service 开发规范
完整规范请参阅项目根目录 AGENTS.md
核心哲学
- AgentOS First — 使用 AgentOS 标准 API，不手写 FastAPI 路由
- Single Agent 优先 — 90% 场景用单 Agent + 工具解决
- 配置与代码分离 — 模型参数用
ModelConfig配置，不硬编码
命名规则
| 元素 | 规则 | 示例 |
|---|---|---|
| Agent ID | kebab-case |
github-analyzer |
| 文件名 | snake_case.py |
github_analyzer.py |
| 类名 | PascalCase |
GitHubAnalyzer |
| 函数/变量 | snake_case |
analyze_repo |
关键规则
性能
- 禁止在循环中创建 Agent，Agent 实例是重量级对象
- 创建一次，复用多次
模型配置
- 使用
app/models/ModelConfig统一接口 - OpenRouter 是主要模型提供商
- 切换模型只需修改
ModelConfig
API Key 优先级
- Agent 级:
ModelConfig(api_key_env="XXX_KEY") - Project 级:
ProjectConfig(api_key_env="XXX_KEY") - Global 级:
OPENROUTER_API_KEY环境变量
代码风格
- 禁止在 print/log 中使用 emoji
- 工具函数返回 str，让模型处理
- 新 Agent 必须在
app/agents/__init__.py注册
常见错误
- 手写 FastAPI 路由（应让 AgentOS 自动生成）
- 在环境变量里配置模型参数（应在代码中用 ModelConfig）
- 使用 Team 解决单 Agent 能处理的任务
- 忘记在
__init__.py注册新 Agent
快速参考
# Agent 模板
from app.models import ModelConfig, create_model
AGENT_MODEL_CONFIG = ModelConfig(
model_id="google/gemini-2.5-flash-preview-09-2025",
temperature=0.1,
max_tokens=16384,
)
def create_my_agent(db: PostgresDb) -> Agent:
return Agent(
id="my-agent",
model=create_model(AGENT_MODEL_CONFIG),
db=db,
instructions=SYSTEM_PROMPT,
tools=[...],
)
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.
- 4d ago First seen · 74 lines · 0 tokens per session scan A db90f2fd2fe9
global is a cursor rule published in the GitHub repository linhai0872/agno-agent-starter (6 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 577 tokens. 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 cursor rules, from other repositories
agents
Единые правила и скиллы проекта (зеркало AGENTS.md).
cursorrules
You are an AI agent building the module: {{MODULENAME}} This module is part of the Mnemosyne Neural OS ecosystem by XPACEGEMS LLC.
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.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.