perceiving-objects-oneshot
perceiving-objects-oneshot is a Computer vision skill for AI agents, published by graph-robots in the open-robot-skills repository on GitHub. Skillspace rates perceiving-objects-oneshot C (78/100) and it passed the safety scan; the rating is based on static analysis only.
Lightweight one-shot 3D object perception. Runs Grounding-DINO broad detection, a SINGLE VLM set-of-marks letter pick over the labeled boxes, SAM3 box segmentation, depth back-projection, and geometry.filter_and_compute_obb. No pairwise tournament, no multi-view safe-gate. Returns a clean not_found output (no exception) when the VLM answers "none" or DINO emits no detections — making this the right skill for clean-all-items loops whose natural termination signal is "no more matching objects in view". Use when a multi-item loop needs a clean no-match exit, or for generic target descriptions on uncluttered scenes with reasonably sized targets.
- Grade
- C
- Quality
- 78 / 100
- Safety
- Passed
- GitHub stars
- 22
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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