RocketRide is an open-source AI development environment and data-pipeline runtime that lets developers compose, debug, observe, and deploy model-based workflows from an IDE or terminal. Its C++ engine runs portable pipelines with extensible nodes for language models, vector databases, document processing, and agent orchestration on the user's infrastructure. The catalogue entries relate to operating and developing with RocketRide's workflows, SDKs, and tooling.
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/rocketride-org/rocketride-serverWrote 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/rocketride-org/rocketride-server/cursor)<a href="https://agentmods.dev/rules/rocketride-org/rocketride-server/cursor"><img src="https://agentmods.dev/badge/rules/rocketride-org/rocketride-server/cursor/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/rocketride-org/rocketride-server/cursor"><img src="https://agentmods.dev/badge/rules/rocketride-org/rocketride-server/cursor.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 | $0.00000 | $0.00876 |
| Opus 5.5 | $0.00000 | $0.00350 |
| Sonnet 5.5 | $0.00000 | $0.00175 |
| Haiku 4.5 | $0.00000 | $0.00088 |
Grade A, and why
cursor 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.
How it starts
The opening of the file, as written. The whole thing — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RocketRide: AI Pipeline & App Platform
Use RocketRide when building AI pipelines (document processing, RAG, agents, data integration) or when building apps on the RocketRide platform (React UIs on the platform shell, often embedding pipelines).
Documentation
Full docs: .rocketride/docs/
Read the relevant doc(s) before generating any RocketRide code.
| File | Read when... |
|---|---|
| ROCKETRIDE_README.md | Starting ANY RocketRide work: the platform map, setup, task router |
| ROCKETRIDE_CLI.md | The rocketride command: validate, start/upload runs, store, deploy, app verbs; when to prefer it over SDK code |
| ROCKETRIDE_CONCEPTS.md | Early, always: workspace, connection, deploy/publish lifecycle, how apps and pipelines fit together |
| ROCKETRIDE_PIPELINES.md | Writing or editing a .pipe: format, lanes, profiles, patterns, pitfalls |
| ROCKETRIDE_COMPONENT_REFERENCE.md | Choosing/configuring pipeline components via the catalog + schemas |
| ROCKETRIDE_APPS.md | Building or modifying an app: App Builder, shell UI, manifest, deploy/publish |
| ROCKETRIDE_UI_COMPONENTS.md | Using a specific UI component in an app: props, wiring, snippets |
| ROCKETRIDE_INTEGRATIONS.md | MCP tools, n8n, external webhooks, Telegram, mid-pipeline HTTP, CI |
| ROCKETRIDE_python_API.md | Python SDK: client methods, deploy & schedules, file store, events |
| ROCKETRIDE_typescript_API.md | TypeScript SDK: client methods, app-sdk, deploy & schedules, events |
| ROCKETRIDE_OBSERVABILITY.md | Consuming runtime events and logs, building monitoring |
Before writing ANY RocketRide code
- Read
.rocketride/docs/ROCKETRIDE_README.mdand follow its task router for the job at hand - Building a pipeline: ROCKETRIDE_CONCEPTS.md + ROCKETRIDE_PIPELINES.md + ROCKETRIDE_COMPONENT_REFERENCE.md
- Building an app: ROCKETRIDE_CONCEPTS.md + ROCKETRIDE_APPS.md + ROCKETRIDE_UI_COMPONENTS.md
- Driving either from code: NEVER invent anything — verify
client.*method names and signatures against your language's API doc (ROCKETRIDE_python_API.md/ROCKETRIDE_typescript_API.md), and pipeline component names and config fields against.rocketride/services-catalog.jsonand.rocketride/schema/ - Two connections may exist in
.env:ROCKETRIDE_URI/ROCKETRIDE_APIKEY(development - run/validate/iterate) andROCKETRIDE_DEPLOY_URI/ROCKETRIDE_DEPLOY_APIKEY(deployment target - deploy/publish/schedule). Never run lifecycle verbs against the dev pair; if the DEPLOY pair is absent, no deploy target is configured - ask the user. - NEW apps are created ONLY through the scaffold - agents call
client.deploy.createApp(slug, ...)(install the client first from the workspace's own.rocketride/client/rocketride.tgz- the scaffold vendors it from the connected server, so it is present once the workspace has been opened against one; with no server URL known the scaffold skips vendoring and the tarball lands on the next connected open - NEVER from the npm registry); humans use the App Builder's New App wizard. Never hand-create app files. (For lifecycle operations generally, prefer therocketridecommand; see ROCKETRIDE_CLI.md.)
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 Changed · +1 lines 551eabc2bf53
- 1mo ago Changed · +6 lines caffe6c888c9
- 1mo ago First seen · 34 lines · 0 tokens per session scan A b683c745fef3
cursor is a cursor rule published in the GitHub repository rocketride-org/rocketride-server (17,764 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 876 tokens. 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
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.
scripts
Utility scripts for development and CI/CD.
zenml-domain-models
How to understand, add or modify ZenML domain models.
mod-003c-missing-required-class-docstring-sections
Class docstrings must contain three mandatory sections - Parameters, Forward, and Outputs. Optional sections include Notes, Examples, ..important::, and ..code-block::.
mod-003f-callback-functions-must-have-code-block-specification
Callback function parameters must include a ..code-block:: specification showing the required signature and return type, placed outside Parameters/Forward/Outputs sections.
mod-001-use-physicsnemo-module-as-base-class
All model and layer classes must inherit from physicsnemo.Module (not torch.nn.Module directly) to ensure proper serialization, versioning, and registry functionality.