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 graph-robots/open-robot-skills --skill grounding-dinogit clone --depth 1 https://github.com/graph-robots/open-robot-skillsWrote 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/graph-robots/open-robot-skills/grounding-dino)<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/grounding-dino"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grounding-dino/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/graph-robots/open-robot-skills/grounding-dino"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grounding-dino.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 | $0.00049 | $0.00583 |
| Opus 5 | $0.00024 | $0.00292 |
| Sonnet 5 | $0.00010 | $0.00117 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
grounding-dino 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 10d 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
grounding-dino
The Grounding DINO servicer (IDEA-Research/grounding-dino-base via
transformers) as one in-process tool. Image in: RGB uint8 [H, W, 3] numpy
array; out: {detections: [{box, label, score}, ...]}.
When to use
- Locating a named object in a camera frame:
grounding-dino.detect(rgb, "cream cheese box."), pick the best box (highest score, or closest to a pointing-model pixel), thensam3.segment_boxfor a pixel-accurate mask. - Empty
detectionsmeans nothing cleared the thresholds — treat as not-found, don't retry blindly with the same prompt.
Install
uv sync --extra grounding-dino # torch + transformers
# (pip: pip install -e ".[grounding-dino]")
Weights download from HuggingFace on first call. Env knobs:
GAP_DINO_DEVICE (default cuda; CPU works but is slow) and
GAP_DINO_MODEL (default IDEA-Research/grounding-dino-base).
Gotchas (carried over from the servicer)
- Period-separated phrases: GDINO's text encoder expects each object
phrase terminated with
.("red cube. green cube."). A missing final period is appended automatically, but separate multiple objects yourself. - Default thresholds are deliberately low (0.20/0.20) for recall on household objects; raise them when false positives leak through. Zero or negative thresholds fall back to the defaults (proto-default semantics).
labelstrings are the matched text spans, not your full query — when querying multiple phrases, group detections by label.- The model is a lazy module-level singleton; the first call pays the weights-load latency, subsequent calls don't.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 57 lines · 49 tokens per session scan A de0c5fe59200
grounding-dino is a skill published in the GitHub repository graph-robots/open-robot-skills (41 stars, last pushed yesterday), licensed Apache-2.0. It adds 49 tokens to every session and 583 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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