AGNO_Structured

Guidance for making AGNO agents return structured data using Pydantic models, Python definitions that describe required fields and types.

In plain words
What is it for?
Use it when AGNO output must follow a defined data format.
Why use it?
It helps keep responses predictable so other parts of an application can check and use them.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/aiflowml/cursor_rules/agno_structured
Clone the repo
git clone --depth 1 https://github.com/AIFlowML/cursor_rules

Made for: Cursor.

Per session 14 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,488 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. Scan, not verified.
Origin unknown 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 $0.00014 $0.04488
Opus 5 $0.00007 $0.02244
Sonnet 5 $0.00003 $0.00898
Haiku 4.5 $0.00001 $0.00449

Measured 2d ago against content hash 271b0bbb4a95, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

AGNO_Structured scanned grade B with 1 finding 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 2d 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.

Asks the agent to reveal its instructionsmediumSystem prompt leakage

Directions to print, repeat or translate the system prompt extract configuration the operator did not intend to expose.

# Help the model succeed with structured output instructions=[
.cursor/rules/AGNO/AGNO_Structured.mdc · 528 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 2d ago First seen · 528 lines · 14 tokens per session scan B 271b0bbb4a95

Subscribe to this mod's changes

AGNO_Structured is a cursor rule published in the GitHub repository AIFlowML/cursor_rules (25 stars, last pushed 1y ago), with no licence file. It adds 14 tokens to every session and 4,488 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (asks the agent to reveal its instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.