grasping-concave-contour

grasping-concave-contour is a skill for Claude Code, Codex from graph-robots/open-robot-skills. It costs 130 tokens per session (1,203 once invoked), scanned A, original, Apache-2.0.

A robot-grasp planning procedure for rigid objects whose outlines have inward curves, such as pliers or gears. It finds pairs of inward points in a camera-derived shape and proposes where parallel gripper jaws should close.

In plain words
What is it for?
Use it to generate and rank grasp poses for awkward rigid parts, while retaining alternative candidates if the first grasp fails.
Why use it?
It handles objects where a simple long-axis or rectangular bounding-box method cannot find suitable opposing surfaces.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to generate and rank grasp poses for awkward rigid parts, while retaining alternative candidates if the first grasp fails.

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Install with agentmods
npx agentmods add skills/graph-robots/open-robot-skills/grasping-concave-contour
Install

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.

Any agent
npx skills add graph-robots/open-robot-skills --skill grasping-concave-contour
Clone the repo
git clone --depth 1 https://github.com/graph-robots/open-robot-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for grasping-concave-contour

README.md
[![agentmods](https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-concave-contour/github.svg)](https://agentmods.dev/skills/graph-robots/open-robot-skills/grasping-concave-contour)
Your own site
<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.

agentmods 80×15 button for grasping-concave-contour

Your own site · 80×15
<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>
Per session 130 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,203 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash 24c40b77ba53, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/contour_concave_grasp.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/grasping-concave-contour/SKILL.md · 100 lines

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

  1. Projects the segmented cloud to the (x, y) plane the part is seen from.
  2. 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.
  3. 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.
  4. 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.
  5. Ranks by confidence and returns the best, with the rest in candidates so 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.

Files

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.

Changes

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.

  1. 1mo ago First seen · 100 lines · 130 tokens per session scan A 24c40b77ba53

Subscribe to this mod's changes

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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