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 gemini-ergit 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/gemini-er)<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/gemini-er"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/gemini-er/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/gemini-er"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/gemini-er.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 | $0.00065 | $0.00629 |
| Opus 5 | $0.00032 | $0.00315 |
| Sonnet 5 | $0.00013 | $0.00126 |
| Haiku 4.5 | $0.00006 | $0.00063 |
Grade A, and why
gemini-er 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 9d 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
gemini-er
API-backed 2D detection on Gemini Robotics-ER. Zero GPU. The canonical
perception recipe (from the dev tree's perceive_gemini_er workflow script)
is: gemini-er.detect → best box by score → sam3.segment_box on the full
frame at that box → depth projection → OBB fit.
Install
uv sync --extra gemini-er # google-genai (pip: pip install -e ".[gemini-er]")
export GOOGLE_API_KEY=... # or GEMINI_API_KEY
Config
| Env | Meaning | Default |
|---|---|---|
GAP_GEMINI_ER_MODEL |
Gemini model name | gemini-robotics-er-1.5-preview |
GOOGLE_API_KEY / GEMINI_API_KEY |
API key (SDK default resolution) | — |
Contract
gemini-er.detect(image, query) returns
{"detections": [{"box": BoundingBox2D, "label": str, "score": float}]}:
boxis pixel-space{x1, y1, x2, y2}(top-left → bottom-right), clamped to the image bounds. The model emits the Geminibox_2dconvention ([ymin, xmin, ymax, xmax]normalized 0–1000); conversion happens here.scoredefaults to 1.0 when the model reports none — callers select the best detection withmax(..., key=score).- No match (or unparseable model output) → empty
detections, never an error. Treat empty as "object not visible".
When to use
- Detection boxes for open-vocabulary prompts, no local weights.
- Prefer
molmo.point_promptwhen a single click point is enough, andvlm.query_yes_nofor semantic checks without localization.
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.
- 9d ago First seen · 58 lines · 65 tokens per session scan A 391731d845f1
gemini-er is a skill published in the GitHub repository graph-robots/open-robot-skills (40 stars, last pushed today), licensed Apache-2.0. It adds 65 tokens to every session and 629 once invoked, about $0.0003 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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