Install
$ agentstack add skill-graph-robots-open-robot-skills-molmo ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
molmo
Molmo visual pointing + Q&A. The bundle itself is zero-GPU (httpx client only), but Molmo has no hosted API — you must serve it yourself with vLLM and point GAP_MOLMO_BASE_URL at it. If you can't self-host, use gemini-er.detect (hosted Gemini Robotics-ER) instead.
Hosting recipe (vLLM)
Lifted from the dev tree's run book (training/README.md):
# Serve Molmo2-8B on an OpenAI-compatible endpoint
CUDA_VISIBLE_DEVICES=0 PYTHONNOUSERSITE=1 \
python -m vllm.entrypoints.openai.api_server \
--model allenai/Molmo2-8B \
--trust-remote-code \
--dtype bfloat16 \
--port 8122 \
--gpu-memory-utilization 0.5 \
--max-model-len 4096 \
--max-num-batched-tokens 4096
# Smoke-test
curl -s http://127.0.0.1:8122/v1/models | jq '.data[0].id'
# Point the bundle at it
export GAP_MOLMO_BASE_URL=http://127.0.0.1:8122/v1
Operational notes from the dev tree: pin Molmo to its own GPU when running alongside other perception services — under heavy parallel evaluation it becomes the throughput bottleneck if co-located; on a dedicated GPU you can push --gpu-memory-utilization 0.85 --max-num-batched-tokens 8192 for ~2× perception throughput. The server can also run on a remote machine and be port-forwarded in (the 4090 real-robot profile did exactly this).
Config
| Env | Meaning | Default | |----------------------|--------------------------------------|----------------------| | GAP_MOLMO_BASE_URL | vLLM OpenAI-compatible base URL | — (required) | | GAP_MOLMO_MODEL | Model name served by vLLM | allenai/Molmo2-8B |
Notes
molmo.point_promptsends the canonical"Point at "prompt and
parses all four Molmo point output formats (Molmo2 `, Molmo1 , legacy , plain x, y fallback), converting normalized coordinates to pixels. found=False` means the model emitted no parseable point.
molmo.query_yes_nocoerces with the source-verbatim rule: answer is true
iff "yes" appears in the lowercased reply.
- Backend unreachable after 3 retries raises
ToolError(routeon_error).
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: graph-robots
- Source: graph-robots/open-robot-skills
- License: Apache-2.0
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.