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/panishandsome/ai-rules-sync/cursorrulesgit clone --depth 1 https://github.com/PanisHandsome/ai-rules-syncWhat 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 | $0.00120 | $0.00120 |
| Opus 5 | $0.00060 | $0.00060 |
| Sonnet 5 | $0.00024 | $0.00024 |
| Haiku 4.5 | $0.00012 | $0.00012 |
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 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.
What it actually says
You are working in a Python 3.12 FastAPI service.
- Install deps with
uv sync. - Run the dev server with
uv run fastapi dev. - Run tests with
uv run pytest. - Format and lint with
uv run ruff check --fix.
Conventions:
- Use type hints everywhere; the project runs mypy in strict mode.
- Pydantic v2 models for all request/response bodies.
- Keep route handlers thin; put business logic in
app/services/.
Never commit secrets. Do not edit anything under app/migrations/.
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 · 14 lines · 120 tokens per session scan A 26ead176e226
cursorrules is a cursor rule published in the GitHub repository PanisHandsome/ai-rules-sync (118 stars, last pushed 3mo ago), licensed MIT. It adds 120 tokens to every session, about $0.0006 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 2026-08-30.
Other cursor rules, from other repositories
repo
Repository-specific AI coding rules generated by repo2agent.
architecture-constraints
GolemBot architecture hard constraints — must check before modifying any src/ code.
git-commit-attribution
Git commits must use the human developer identity only; never Cursor Agent co-authorship.
skill-creator
Create, edit, evaluate, and debug the skills in this repo, including running their evals and fixing a description that fails to trigger. Use when user says 'help me build a new skill', 'add a skill for X', 'run the evals for the tf skill', 'run the behavioral evals', 'my skill is not triggering', 'fix this skill's…
java-springboot-jpa-cursorrules-prompt-file
description: "Cursor rules for Java development with Springboot and JPA integration." globs: / alwaysApply: false.
tf-plan
Review a Terraform plan before applying it: destroys and replacements of data-bearing resources, secrets readable in plan output, out-of-band drift, blast radius, and whether the apply is bound to the plan you actually reviewed. Use when user says 'review my plan', 'is this plan safe to apply', 'check tfplan', 'what…