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.
git clone --depth 1 https://github.com/vb-nattamai/agent-readyWrote 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/vb-nattamai/agent-ready/cursorrules)<a href="https://agentmods.dev/rules/vb-nattamai/agent-ready/cursorrules"><img src="https://agentmods.dev/badge/rules/vb-nattamai/agent-ready/cursorrules/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/rules/vb-nattamai/agent-ready/cursorrules"><img src="https://agentmods.dev/badge/rules/vb-nattamai/agent-ready/cursorrules.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00232 | $0.00232 |
| Opus 5.5 | $0.00093 | $0.00093 |
| Sonnet 5.5 | $0.00046 | $0.00046 |
| Haiku 4.5 | $0.00023 | $0.00023 |
Grade A, and why
cursorrules 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 1mo 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
hello_world
Project overview
A minimal Flask REST API that provides personalised greetings, records them in memory, and exposes health-check and listing endpoints.
Language and framework
- Primary language: Python
- Framework: Flask, pytest
- Build system: pip
Critical commands
- Install: pip install -r requirements.txt
- Build: pip install -e '.[dev]' 2>/dev/null || pip install -r requirements.txt
- Test: pytest
- Run locally: python app.py
Code conventions
Naming: snake_case Structure: single-package Source directories: .
Files and directories
- Entry point: app.py
- Tests: tests
Do not modify
Not determinable from source — fill in agent-context.json static.restricted_write_paths
Domain concepts
- Greeting: A recorded personalised message containing a user's name and a hello message, stored in the in-memory list.
- Health Check: A lightweight endpoint (/health) that returns an 'ok' status to confirm the service is running.
- Service Root: The index endpoint (/) that returns the service name and version metadata.
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.
- 1mo ago First seen · 33 lines · 232 tokens per session scan A 0a597fd1de15
cursorrules is a cursor rule published in the GitHub repository vb-nattamai/agent-ready (5 stars, last pushed 2mo ago), licensed MIT. It adds 232 tokens to every session, about $0.0009 per session on Opus 5.5. 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 cursor rules, from other repositories
python
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python_tests
We use the unit tests to cover internal behavior that can work without the web / backend counterpart. We aim for 95%+ unit test coverage of our Python code in lib/streamlit.
django-python
Rules for writing Python services at PostHog (Python servers powered by the Django framework).
py-fast-api
Cursor rules for Python FastAPI backend development and best practices.
python
Python best practices and patterns for modern software development with Flask and SQLite.
python--typescript-guide-cursorrules-prompt-file
Cursor rules for Python development with TypeScript guide integration.