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/marlondivino/open-code-as-mcp/cursorrulesgit clone --depth 1 https://github.com/marlondivino/open-code-as-mcpWhat 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 | $0.00135 | $0.00135 |
| Opus 5 | $0.00068 | $0.00068 |
| Sonnet 5 | $0.00027 | $0.00027 |
| Haiku 4.5 | $0.00014 | $0.00014 |
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 3d 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
Antigravity Global Rules
- Prompt Refinement: Whenever the user sends a request, first announce to the user: "Refining your request with OpenCode for technical precision...", then use
opencode:refine_prompt. - Context Enrichment: Upon receiving the refined prompt, validate if there are technical terms or project patterns that require additional lookup in semantic memory. Mention if you are pulling specific context from OpenCode memory.
- Continuous Learning: After successfully implementing a complex feature, use
opencode:learn_context. Briefly inform the user that this knowledge is being persisted in OpenCode's semantic memory.
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.
- 3d ago First seen · 6 lines · 135 tokens per session scan A 2d79583e857e
cursorrules is a cursor rule published in the GitHub repository marlondivino/open-code-as-mcp (6 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 135 tokens to every session, about $0.0007 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
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
cli-error-handling
CLI command error handling patterns.
prefer-direct-imports-over-module-mocks
Prefer extracting a testable core over vi.mock / vi.resetModules when unit tests need to reach production logic entangled with config, env, or singletons.
control-plane-descriptors
Control plane descriptor and instance implementation patterns.
family-instance-domain-actions
Family instance domain action implementation patterns.