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.
npx skills add rocketride-org/rocketride-server --skill rocketride-debugging-pipelinesgit 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/skills/rocketride-org/rocketride-server/rocketride-debugging-pipelines)<a href="https://agentmods.dev/skills/rocketride-org/rocketride-server/rocketride-debugging-pipelines"><img src="https://agentmods.dev/badge/skills/rocketride-org/rocketride-server/rocketride-debugging-pipelines/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/skills/rocketride-org/rocketride-server/rocketride-debugging-pipelines"><img src="https://agentmods.dev/badge/skills/rocketride-org/rocketride-server/rocketride-debugging-pipelines.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 | $0.00067 | $0.01134 |
| Opus 5.5 | $0.00027 | $0.00454 |
| Sonnet 5.5 | $0.00013 | $0.00227 |
| Haiku 4.5 | $0.00007 | $0.00113 |
Grade A, and why
rocketride-debugging-pipelines 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.
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debugging RocketRide Pipelines
Diagnose, don't guess. A failed run has a real cause in the status/trace; find it, then route the fix to the right phase. No re-running until the cause is identified and the fix is validated.
Procedure
- Read the status. MCP:
monitor(task_token)→ quotestate_label,errors[],warnings[],countsverbatim. SDK:get_task_status(token)→state,errors[],warnings[],exitCode,exitMessage,failedCount. Don't paraphrase error messages. - Read the trace. MCP — the run-log (DVR) tools work for past and live runs, keyed by the
projectId+sourcereturned byrun_pipeline/run_dropper_pipe(never the task token):log_chaptersto find the run →log_readfor paged events (≤200/page; follow the cursor) →log_tracesto list per-object traces →log_tracefor one object's full per-nodeenter/leavewithlane,data,result,error. Retention: 7 days dev / 30 days deploy. A run started withpipelineTraceLevel="none"has chapters/console but empty traces — re-run with"summary"/"full"for flow evidence. SDK fallback: theapaevt_flow/_traceevents in the response. Either way, find the first node whose op shows an error or whose output is empty/wrong — that's the failure point. Downstream errors are usually consequences. - Classify the cause (see
ERROR_TABLE.md):- Config — bad/missing field, wrong API key, wrong model name → fix in
rocketride-configuring-pipelines(re-fetch schema, re-validate). - Wiring/lane — lane mismatch, missing converter, wrong source method → fix in
rocketride-designing-pipelines(re-wire), then re-configure + re-validate. - Runtime — event-loop blocked (
Connection closed/timeout),Pipeline already running, blocking I/O → fix the run code inrocketride-running-pipelines. - Data — empty/garbage input, wrong response key (
KeyError) → check input +result_types.
- Config — bad/missing field, wrong API key, wrong model name → fix in
- Propose a specific fix tied to the evidence: "Node
llm_1failed:Invalid API key. The${ROCKETRIDE_OPENAI_KEY}env var is unset / wrong. Fix: set it, re-validate, re-run." Route to the owning phase. Do not re-run until the fix is made andvalidate()is clean again.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 Changed · +1 lines 0e9f190e5e0e
- 25d ago First seen · 63 lines · 67 tokens per session scan A 3bf4491b8a97
rocketride-debugging-pipelines is a skill published in the GitHub repository rocketride-org/rocketride-server (17,809 stars, last pushed today), licensed MIT. It adds 67 tokens to every session and 1,134 once invoked, about $0.0003 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 2026-09-15.
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