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/ucsahinn/ai-project-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/ucsahinn/ai-project-starter/cursor-project)<a href="https://agentmods.dev/rules/ucsahinn/ai-project-starter/cursor-project"><img src="https://agentmods.dev/badge/rules/ucsahinn/ai-project-starter/cursor-project/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/ucsahinn/ai-project-starter/cursor-project"><img src="https://agentmods.dev/badge/rules/ucsahinn/ai-project-starter/cursor-project.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 | $0.00119 | $0.00119 |
| Opus 5.5 | $0.00048 | $0.00048 |
| Sonnet 5.5 | $0.00024 | $0.00024 |
| Haiku 4.5 | $0.00012 | $0.00012 |
Grade A, and why
cursor-project 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 2mo 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
Follow AGENTS.md as the shared project instruction source.
Before coding, read the current task plus the relevant project docs:
PROJECT_BRIEF.mdPRODUCT_REQUIREMENTS.mdTECHNICAL_SPEC.mdARCHITECTURE.mdQUALITY_GATES.md
Keep changes inside the current milestone. Do not add duplicate systems, broad refactors, new dependencies, deployments, commits, pushes, releases, or security boundary changes without explicit approval.
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.
- 2mo ago First seen · 17 lines · 119 tokens per session scan A 774098ca1b26
cursor-project is a cursor rule published in the GitHub repository ucsahinn/ai-project-starter (6 stars, last pushed 3mo ago), licensed MIT. It adds 119 tokens to every session, about $0.0005 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
keep-the-why
In a project that uses Keep the Why (a .keep-the-why file at the workspace root, or a legacy keep-the-why:config block in AGENTS.md), load the keep-the-why skill first. Anywhere else, leave the skill alone.
error-handling-and-validation
A code-quality guide for handling errors, invalid inputs, edge cases, preconditions, logging, and user-friendly error messages.
error-handling-priorities
General rules for handling errors in code, including early checks, guard clauses, logging, user-friendly messages, and custom error types.
python-general-coding-standards
A set of general standards for Python projects, including type hints, input checking, code style, security, web requests, background work, and tests. It also covers FastAPI-specific tasks such as CORS and authentication.
monorepo-and-tooling
Rules for projects that may use a monorepo, a single repository containing multiple applications or shared packages. They also define Taskfile commands and how to keep environment settings outside the code.
check-x-md-content-rule
A rule that requires checking whether the contents of an x.md file are valid before using them.