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-with-plannergit 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-with-planner)<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/grasping-with-planner"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-with-planner/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-with-planner"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-with-planner.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 | $0.00139 | $0.02833 |
| Opus 5 | $0.00069 | $0.01417 |
| Sonnet 5 | $0.00028 | $0.00567 |
| Haiku 4.5 | $0.00014 | $0.00283 |
Grade A, and why
grasping-with-planner 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
grasping-with-planner
Top-down grasping with a fast axis-locked linear descend and a
collision-aware cuRobo fallback. The primary path rises to a hover height,
translates over the target while rotating to the grasp yaw, and descends
straight down (Z-only, orientation locked) onto the object — which, unlike a
goalset planner, happily grips a flat object by simply lowering onto it. If
the straight-line solve is infeasible, the same node hands off to the cuRobo
planner, which builds a per-observation collision world and searches the whole
candidate fan for a reachable, collision-free wrist. This is the
grocery_packing grasp motion, distilled to the general single-object case.
Install
This skill depends on the curobo tool bundle (curobo.plan_directed_linear,
curobo.plan_to_grasp_poses). cuRobo JIT-compiles CUDA extensions at install
time — build isolation must be off and CUDA_HOME must point at a toolkit
matching your torch build:
export CUDA_HOME=/usr/local/cuda
uv sync --extra curobo # (pip: pip install -e "open-robot-skills[curobo]" --no-build-isolation)
See tools/curobo/SKILL.md for the full recipe and gotchas.
When to use
- Default grasping skill whenever
curobois deployed — clean or cluttered. - Flat / low-profile objects (a butter box, cream cheese) where a goalset planner struggles but a straight lower-on-top succeeds.
When NOT to use
curobonot deployed. Usegrasping-direct-ikinstead.- The graspable region is NOT the OBB centroid — bowl rim, mug / moka-pot /
frying-pan handle, or any off-center grasp. The OBB top-down candidates from
geometry.top_down_grasp_candidatesare centered on the OBB XY, so they slip on hollow centers and miss handles. Usegrasping-short-axisfor elongated handles, where the centroid is graspable but orientation is what matters.
Recommended subgraph state flow
6 states, in order:
open → compute_grasp → goto_grasp → observe → close → grasped
What ships with it
9 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.
- examples/canonical_subgraph.json 1.4 KB
- references/design_grasp_curobo.md 1.7 KB
- references/gripper_settle_constants.md 1.2 KB
- scripts/approach_above.py 2.4 KB runs code
- scripts/build_world.py 2.2 KB runs code
- scripts/compute_align_pose.py 1.0 KB runs code
- scripts/grasp_descend_linear.py 19 KB runs code
- scripts/plan_grasp.py 2.6 KB runs code
- scripts/select_short_axis.py 4.0 KB runs code
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.
- 11d ago First seen · 225 lines · 139 tokens per session scan A c800ad6e389a
grasping-with-planner is a skill published in the GitHub repository graph-robots/open-robot-skills (41 stars, last pushed yesterday), licensed Apache-2.0. It adds 139 tokens to every session and 2,833 once invoked, about $0.0007 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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