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 commands/generous-corp/pulp/gpugit clone --depth 1 https://github.com/Generous-Corp/pulpWrote 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/commands/generous-corp/pulp/gpu)<a href="https://agentmods.dev/commands/generous-corp/pulp/gpu"><img src="https://agentmods.dev/badge/commands/generous-corp/pulp/gpu.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.00355 |
| Opus 5 | $0.00010 | $0.00178 |
| Sonnet 5 | $0.00004 | $0.00071 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
gpu 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 today.
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
Start with the cheapest truthful path:
pulp doctor gpu --json
pulp gpu recipes list --json
pulp gpu recipes list --symptom <exact-symptom-token> --json
pulp gpu recipes show <recipe-id> --json
Then run the selected closed recipe into a new path-confined artifact directory:
pulp gpu probe --recipe <recipe-id> --artifacts /tmp/pulp-gpu-evidence --json
Exit 0 is a measured pass, exit 1 is a completed measured failure, and exit 2
is unavailable or unverified. Runtime, internal-validation, and artifact
publication failures also use typed unverified JSON and exit 2; never read
them as completed measurements. Preserve the typed JSON, gpu_evidence_id,
adapter status/class, numeric oracle, and artifact digests. An unknown or
unverified adapter is not an authentic hardware claim, even when the backend is
Dawn/WebGPU. Never infer correctness from a screenshot alone.
Use --negative-control only to prove that the declared mutation fails for its
intended causal reason. Do not run GPU readback, validation, or artifact writing
on an audio thread. For a correlated trace, capture through the canonical
exact-instance trace lifecycle and use /trace with gpu-probe over the same
flushed .pftrace.
The recipe catalog is Pulp's product/tool workflow. It does not authorize a generic rendering API or a DPR policy; those remain evidence-gated Vellum follow-up work.
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.
- today First seen · 38 lines · 20 tokens per session scan A 20b01465844c
gpu is a command published in the GitHub repository Generous-Corp/pulp (16 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 355 once invoked, about $0.0001 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 2026-09-04.
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