runpod
Skill93 starsChanged 3 months agoMITView on GitHub
Provision, diagnose, and clean up paid RunPod compute for robotics workloads.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- pytorch/heliontheir own version, first seen Nov 8, 2026
- digitalsamba/claude-code-video-toolkittheir own version, first seen Nov 8, 2026
- beyarkay/claude-skillstheir own version, first seen Jul 16, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- digitalsamba/claude-code-video-toolkit★ 2.5ksame name
- pytorch/helion★ 979same name
- beyarkay/claude-skills★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository32 other files it gives its agents.
- AGENTS.mdAGENTS.md
- learnings/AGENTS.mdAGENTS.md
- skills/AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- learnings/CLAUDE.mdCLAUDE.md
- skills/CLAUDE.mdCLAUDE.md
- app-publishingSkill
- architectSkill
- cloud-runSkill
- dataSkill
- environmentsSkill
- foxgloveSkill
- gazeboSkill
- gemini-roboticsSkill
- huggingfaceSkill
- integrationSkill
- isaac-labSkill
- isaac-simSkill
- learning-loopSkill
- lerobotSkill
- live-demoSkill
- miningSkill
- mujocoSkill
- navigationSkill
- rerunSkill
- ros2Skill
- rviz2Skill
- simulationSkill
- skill-authorSkill
- test-assetsSkill
- testingSkill
- visualizationSkill
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Treat the allocated Pod, not the submitted request, as the resource contract.
- Distinctive: line 16
Verify current CLI or API fields against official RunPod documentation.
- Distinctive: line 22
Read provisioning.md when selecting an interface, attaching a network volume, or creating a Pod.
- Distinctive: line 30
Never print full environment maps or authenticated resource objects.
- Distinctive: line 32
Delete a mismatched Pod after preserving safe evidence.
- Distinctive: line 52
Use at most one explicitly approved, time-bounded interactive Pod to isolate application defects.
- Distinctive: line 66
Delete temporary Pods and verify the authoritative Pod list.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
RunPod
Treat the allocated Pod, not the submitted request, as the resource contract.
Before allocating
- Define the workload acceptance test, minimum compute, immutable image, storage, placement, ports, budget, deadline, and cleanup responsibility.
- Inspect balance, existing Pods, volumes, live inventory, prices, and volume locality without creating anything.
- Verify current CLI or API fields against official RunPod documentation; provider interfaces, stock, and prices change.
- Present one exact candidate and obtain explicit approval for that paid resource and lifetime. Failed or mismatched creation does not authorize a series of retries.
- Read provisioning.md when selecting an interface, attaching a network volume, or creating a Pod.
Verify what was created
- Re-read safe fields for the image digest, GPU ID and count, cloud tier, datacenter, volume ID and mount, ports, registry identity, operating mode, price, and termination control.
- Never print full environment maps or authenticated resource objects; they may contain credentials.
- Delete a mismatched Pod after preserving safe evidence. Do not diagnose it as though its requested contract were realized.
Robium observed runpodctl 2.8 accepting volume flags while the resulting Pod
had no network volume, and REST rejecting a live inventory GPU identifier, on
2026-08-24. GraphQL expressed the required contract in that run. This is a
reason to verify provider state, not a universal preference for GraphQL.
For a public service with a shared daily cap, reserve a conservative maximum session cost in an external atomic ledger before Pod creation. Use generation-conditional writes, fail closed on conflicts, and reconcile only controller-owned Pod IDs against final billing. A process-local counter or unconditional object overwrite cannot enforce a multi-instance budget.
Diagnose without guessing
- Combine control-plane state, system logs, container logs, storage identity, durable progress markers, health endpoints, and artifact timestamps.
- A missing runtime, silent container, or repeated start event does not alone distinguish a cold pull, restart loop, provider lag, or application failure.
- Use at most one explicitly approved, time-bounded interactive Pod to isolate application defects. A clean rerun from the rebuilt image digest is the deployment proof; an overlay is not.
- Read diagnostics-and-lifecycle.md for startup classification, proxy validation, evidence, billing, and cleanup.
Finish the allocation
- Validate localhost before the provider proxy, then test authentication and scope boundaries through the public route.
- Download and independently check the evidence before termination.
- Record cost as provider billing, a price-by-lifetime bound, or an observed balance delta; do not blur those measures.
- Delete temporary Pods and verify the authoritative Pod list. Preserve a network volume unless its deletion was explicitly authorized; storage cost continues independently.
- Production enablement is a separate decision from feasibility or cleanup.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

