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 grasping-concave-contourgit 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/grasping-concave-contour)<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/grasping-concave-contour"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-concave-contour/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/grasping-concave-contour"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-concave-contour.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00130 | $0.01203 |
| Opus 5.5 | $0.00052 | $0.00481 |
| Sonnet 5.5 | $0.00026 | $0.00241 |
| Haiku 4.5 | $0.00013 | $0.00120 |
Grade A, and why
grasping-concave-contour 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 1mo 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
Grasping by the concavities in a silhouette
A parallel jaw wants two opposing surfaces. For a handle or a rod, the pair is
implied by the long axis and grasping-linear-feature finds it. For a part with
no long axis — a pair of pliers, a spur gear, a wire spool, a bulb socket — the
opposing surfaces are the waists: the places where the outline turns inward.
This skill finds them directly.
What the script does
- Projects the segmented cloud to the (x, y) plane the part is seen from.
- Builds the alpha shape of that projection — a Delaunay triangulation
filtered to triangles whose circumradius is under
alpha_radius, whose boundary is the part's real outline rather than its hull. - Walks that boundary and keeps the reflex vertices, where it turns inward. Consecutive reflex vertices are one run; each run's centroid is one candidate pad site.
- Pairs the candidates, keeps the pairs whose secant fits the gripper's span, and builds a straight-down pose centred on each pair's midpoint with the jaws closing along the secant.
- Ranks by confidence and returns the best, with the rest in
candidatesso a caller that fails one can try the next without recomputing.
Where it fits
It is a proposer that also poses: it returns grasp_pose and pregrasp_pose
directly rather than handing a list to a selector. Put verifying-grasps after
it — this skill exits posed with the hand open and does not close it — and
route failed to whatever recovery the graph has, because a part whose
silhouette has no fitting pair of waists is one this skill genuinely cannot take.
A sensible arrangement is to try grasping-linear-feature first and fall through
to this on failed: most parts have an axis, and the ones that do not are
exactly the ones this skill is for.
What ships with it
1 file 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.
- 1mo ago First seen · 100 lines · 130 tokens per session scan A 24c40b77ba53
grasping-concave-contour is a skill published in the GitHub repository graph-robots/open-robot-skills (53 stars, last pushed 14d ago), licensed Apache-2.0. It adds 130 tokens to every session and 1,203 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-09-13.
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