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 NVlabs/ASPIRE --skill yam-grasp-pickupgit clone --depth 1 https://github.com/NVlabs/ASPIREWrote 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/nvlabs/aspire/yam-grasp-pickup)<a href="https://agentmods.dev/skills/nvlabs/aspire/yam-grasp-pickup"><img src="https://agentmods.dev/badge/skills/nvlabs/aspire/yam-grasp-pickup/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/nvlabs/aspire/yam-grasp-pickup"><img src="https://agentmods.dev/badge/skills/nvlabs/aspire/yam-grasp-pickup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00284 |
| Opus 5 | $0.00021 | $0.00142 |
| Sonnet 5 | $0.00008 | $0.00057 |
| Haiku 4.5 | $0.00004 | $0.00028 |
Grade A, and why
yam-grasp-pickup 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 12d 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.
What it actually says
YAM Grasp Pickup
Start from fresh live perception. Do not use fixed object XYZ for a physical pickup unless it is explicitly a no-motion calibration run.
Preferred helper layer:
yam_runtime.capture_sceneyam_runtime.generate_side_grasp_candidatesyam_runtime.rank_motion_candidatesyam_runtime.execute_grasp_lift_attemptyam_runtime.staged_close_with_contactyam_runtime.verify_lift
Patterns from current successful scripts:
- Bottle: side body grasp, fixed/biased body Z only after live XY detection, staged close, lift before transport.
- Can: cylinder model, top-down yaw candidates, lift to transfer clearance, verify by post observation.
- Bowl/dish/plate: rim or wall contact, high approach then low pregrasp, gentle staged close, lift only a few centimeters before transport.
- KitKat: top-down endpoint pinch on one short end, then handover the exposed end.
Do not count close command return as pickup success. Require gripper width/contact evidence, lift/post-observation motion, video evidence, or an explicit task artifact.
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.
- 12d ago First seen · 34 lines · 42 tokens per session scan A 8fcebbefbeae
yam-grasp-pickup is a skill published in the GitHub repository NVlabs/ASPIRE (155 stars, last pushed 11d ago), licensed Apache-2.0. It adds 42 tokens to every session and 284 once invoked, about $0.0002 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 2026-08-30.
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