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 skills/nvlabs/aspire/yam-server-setupnpx skills add NVlabs/ASPIRE --skill yam-server-setupgit 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-server-setup)<a href="https://agentmods.dev/skills/nvlabs/aspire/yam-server-setup"><img src="https://agentmods.dev/badge/skills/nvlabs/aspire/yam-server-setup.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 5.1 | $0.00041 | $0.01465 |
| Opus 5 | $0.00020 | $0.00732 |
| Sonnet 5 | $0.00008 | $0.00293 |
| Haiku 4.5 | $0.00004 | $0.00146 |
Grade A, and why
yam-server-setup scanned grade A with 1 finding 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 6d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsS --max-time 3 http://127.0.0.1:6767/health # SAM3 How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YAM Server Setup
Run these checks and launch commands from the Aspire real-robot workspace
(aspire/real). Paths below are relative to that directory.
Process check:
pgrep -af 'run_script.py|ffmpeg|cap.debug_ui.app|arm_server|serve_bundlesdf|serve_real_yam_camera_portal|serve_anygrasp|serve_sam3|follower|curobo|pyroki'
Process presence is only liveness. Before physical demos, verify readiness.
Health/readiness check:
curl -fsS --max-time 3 http://127.0.0.1:6767/health # SAM3
curl -fsS --max-time 3 http://127.0.0.1:8119/health # BundleSDF
curl -fsS --max-time 3 http://127.0.0.1:9600/health # PyRoki
curl -fsS --max-time 3 http://127.0.0.1:8765/health # provider
curl -fsS --max-time 3 http://127.0.0.1:8122/health # AnyGrasp if needed
Portal services are not HTTP health servers; plain curl may reset. Check them
through Portal RPC:
uv run python -c "import portal; print(portal.Client('127.0.0.1:8611').health_check().result(timeout=5))"
uv run python -c "import portal, numpy as np; c=portal.Client('127.0.0.1:8300'); print(c.health().result(timeout=3)); [print(cam, np.asarray(c.get_camera_image(cam).result(timeout=3)).shape) for cam in ['top','left','right','bottom']]"
Arm servers must be healthy, not just connectable. connected=True is
insufficient if the send loop died. Do not run physical motion unless each arm
has send_thread_alive=True and background_error=None:
uv run python -c "import portal, sys; ok=True
for side,port in [('left',11333),('right',11334)]:
h=portal.Client(f'127.0.0.1:{port}').get_health().result(timeout=5)
print(side, h)
ok = ok and bool(h.get('connected')) and bool(h.get('send_thread_alive')) and h.get('background_error') is None
sys.exit(0 if ok else 2)"
BundleSDF and recorder readiness are required before physical debugging runs. Do not start a physical run without video evidence unless the task is explicitly about fixing recording. The command may return success while the run is undebuggable if preview videos are corrupt or missing. Always use the Python preview recorder backend for real runs unless testing the recorder itself:
export OPENFORGE_PREVIEW_RECORDER_BACKEND=python
export OPENFORGE_PREVIEW_RECORDER_PROBE_TIMEOUT_S=8.0
export OPENFORGE_PREVIEW_RECORDER_REENCODE_H264=1
Check BundleSDF health and preview-camera availability:
curl -fsS --max-time 3 http://127.0.0.1:8119/health
The /health response should be status=ok and should list usable preview
cameras such as top, left, right, and bottom. If BundleSDF is unhealthy
or previews are unavailable, fix/restart it before physical motion.
Probe BundleSDF previews before launching long physical runs:
OPENFORGE_PREVIEW_RECORDER_PROBE_TIMEOUT_S=8.0 uv run python -c "from cap.agent.recorder import PreviewStreamRecorder; from pathlib import Path; out=Path('/tmp/yam_preview_probe'); out.mkdir(exist_ok=True); r=PreviewStreamRecorder('http://127.0.0.1:8119',['top','left','right','bottom'],out); r._preflight_preview_streams(); print('preview_preflight_ok')"
After every real run, inspect logs/<run>/preview_recording_result.json.
Accept the videos only when each needed camera has ok=true,
ffprobe.ok=true, nonzero duration_s, nonzero nb_frames, and
backend="python". Current preview MP4s should also report
ffprobe.codec_name="h264" and ffprobe.pix_fmt="yuv420p". The Python
preview recorder writes a temporary OpenCV MP4, preserves it as
<camera>.pre_h264.mp4, and makes <camera>.mp4 the H.264 evidence file by
default. If MP4s are tiny, use mp4v/non-H.264 unexpectedly, or ffprobe
reports moov atom not found, treat the run as missing video evidence even if
robot motion happened.
Mock AnyGrasp may satisfy integration health checks but is not safe for
physical grasp selection. If /health says mock=true or
safe_for_robot_motion=false, only run tasks that do not use AnyGrasp for
physical planning.
Arm servers from the repo root:
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.
- 6d ago First seen · 134 lines · 41 tokens per session scan A 32bb04faa371
yam-server-setup is a skill published in the GitHub repository NVlabs/ASPIRE (127 stars, last pushed 4d ago), licensed Apache-2.0. It adds 41 tokens to every session and 1,465 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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