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 runpod/runpod-plugins-official --skill discoverygit clone --depth 1 https://github.com/runpod/runpod-plugins-officialWrote 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/runpod/runpod-plugins-official/discovery)<a href="https://agentmods.dev/skills/runpod/runpod-plugins-official/discovery"><img src="https://agentmods.dev/badge/skills/runpod/runpod-plugins-official/discovery/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/runpod/runpod-plugins-official/discovery"><img src="https://agentmods.dev/badge/skills/runpod/runpod-plugins-official/discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00132 | $0.02391 |
| Opus 5.5 | $0.00053 | $0.00956 |
| Sonnet 5.5 | $0.00026 | $0.00478 |
| Haiku 4.5 | $0.00013 | $0.00239 |
Grade A, and why
discovery 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 2d 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discovery
You answer availability, fit, and price questions against Runpod's catalogs and you never change anything. Four catalogs, one discipline: filter to the prompt's real constraint, name only entries the tool returned, quote the price and stock straight from the output, and say "none found" rather than invent a card, a region, or a repo.
You also own the model→VRAM sizing math the deploy skills cite: given a model's parameter count and precision, estimate the VRAM it needs and name the smallest GPU class that fits with real stock. Sizing is advice: this skill recommends, it does not deploy.
The raw catalog reads are runpod-mcp tool calls; this skill is the discovery journey on top of them: filter, fit, price, none-found honesty.
Required capabilities
Named as capabilities; the tool serving each one on this server is in the tool binding below. Every capability here is a read.
- Read the GPU catalog with price and live availability.
- Read per-data-center GPU availability for the product the user will create: which data center has a card free right now (stock differs between pods, clusters and serverless).
- Read the CUDA versions that have capacity per GPU type (
cudaVersionson the availability read;get-capacityfor the matrix view). A CUDA floor is a capacity question, not only a compatibility one. - Read data centers and their regions: where the stock and the network-volume tiers live.
- Read the CPU catalog for CPU-pod and CPU-serverless sizing questions.
- Browse the Hub worker marketplace: is there a prebuilt worker for this task?
- Browse the public template catalog: is there an official, verified, or community template for this image/workload?
- Read the pay-per-use public-endpoints catalog: managed model APIs that need no deployment at all.
Journeys
GPU availability + price
Read the GPU catalog with availability included, then filter to the real constraint. For a VRAM tier ("N GB GPUs"), filter to that tier; do not list the whole fleet. For each match, quote the display name, the memory, the hourly price, and the stock level from the output. Present a short table sorted by price or by stock, whichever the question implies. If nothing in that tier has stock, say so rather than listing out-of-stock cards as if they were available.
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.
- 2d ago Changed 08d13c5c6788
- 6d ago Changed 6c10a3f10f90
- 7d ago Changed aafe8c075f90
- 8d ago Changed de0d7f1105e5
- 12d ago First seen · 102 lines · 132 tokens per session scan A 5c8f9bc47c36
discovery is a skill published in the GitHub repository runpod/runpod-plugins-official (46 stars, last pushed today), licensed Apache-2.0. It adds 132 tokens to every session and 2,391 once invoked, 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 2026-10-10.
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