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/vb-nattamai/agent-ready/cursorrulesgit clone --depth 1 https://github.com/vb-nattamai/agent-readyWhat 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 | $0.00232 | $0.00232 |
| Opus 5 | $0.00116 | $0.00116 |
| Sonnet 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 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.
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.
- 2d 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 29d ago), licensed MIT. It adds 232 tokens to every session, about $0.0012 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 cursor rules, from other repositories
1c-coding-standards
Стандарты кода BSL: именование, запросы, коллекции.
1c-skd-two-pass-preprocessing
Двухпроходный СКД: предобработка детальных записей до свертки.
agent-working-memory
Рабочая память агента: файлы плана, передача сессии, журнал инцидентов.
testing-patterns
Паттерны тестирования 1С: YaXUnit, Vanessa.
agents-shipgate
Run Agents Shipgate as the deterministic merge gate for AI-generated agent capability changes.
cursor-tools-mastery
Cursor 3.7 runtime guide: choose the right tool, canvases, Design Mode, /worktree, /best-of-n, Await, and parallel execution where safe.