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-direct-ikgit 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-direct-ik)<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/grasping-direct-ik"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-direct-ik/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-direct-ik"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/grasping-direct-ik.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 | $0.02292 |
| Opus 5 | $0.00069 | $0.01146 |
| Sonnet 5 | $0.00028 | $0.00458 |
| Haiku 4.5 | $0.00014 | $0.00229 |
Grade A, and why
grasping-direct-ik 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 yesterday.
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 — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
grasping-direct-ik
Direct-IK grasp: rotate the gripper to grasp orientation at a safe height above the target, then descend straight down, then close. No trajectory planner — works on platforms where CuRobo is not deployed, or in uncluttered scenes where planning is overkill.
Nothing here is written for one hand. The grasp rotation is composed by the
connector's robot.grasp_frame from the hand's measured approach and closing
axes, the fingertip floor and the hover clearance come from
robot.describe_gripper / robot.describe_workspace, so the same subgraph
grasps the same way on a hand that closes along tool-local x and on one that
closes along tool-local y.
When to use
- The
curobotool bundle is not deployed (no collision-aware planner available). - The scene is uncluttered enough that a straight-line approach is safe.
When NOT to use
- Cluttered scenes where the arm must thread between obstacles. Prefer
grasping-with-plannerif available.
Recommended subgraph state flow
The subgraph state machine the agent generates should look like (7 states):
open → compute_grasp → refine_grasp → compute_align → rotate_align → descend → close → grasped
(grasped is the success-marker noop from sg.add_exit("grasped"),
with an edge to END.)
State details:
open—type: tool,tool: "robot.open_gripper",inputs: { settle_steps: 40 }.compute_grasp—type: tool,tool: "geometry.top_down_grasp_candidates",inputs: { obb: Ref("in.target_obb") }.refine_grasp—type: script, filescripts/<sg>/refine_top_down_grasp.py(from this bundle'scanonical_scripts). Inputs:grasp_pose = Ref("compute_grasp.candidates.poses.0"),target_obb = Ref("in.target_obb"). Returnsgrasp_pose: the candidate with its rotation rebuilt so this hand's closing axis lies across the OBB's short horizontal axis (robot.describe_gripper+robot.grasp_frame(approach=-z, close_heading_deg)), and its Z raised to the fingertip floor (support_z + finger.reach_m + finger.clearance_m) when the hand states its finger envelope. Keep this state: the candidate fan is world-aligned and a thin object's centred grasp jams the jaws on the table without the floor.compute_align—type: script, filescripts/<sg>/compute_align_pose.py. Inputs:grasp_pose = Ref("refine_grasp.grasp_pose"),target_obb = Ref("in.target_obb"), optionallyclearance(a literal in metres). Returnsalign_poseat the grasp XY and rotation, withz = max(obb_top, grasp_z) + clearance. Omitclearance(or pass0) and the script asksrobot.describe_workspaceforalign_clearance_m— the hand's own envelope above the fingertips. Pin it (e.g.0.12) when the held object is what needs the room, such as a long tool that will hang below the fingertips on the way up.rotate_align—type: tool,tool: "robot.go_to_pose",inputs: { pose: Ref("compute_align.align_pose") }.descend—type: tool,tool: "robot.go_to_pose",inputs: { pose: Ref("refine_grasp.grasp_pose") }— the same posecompute_alignwas given, so hover and grasp share one rotation.close—type: tool,tool: "robot.close_gripper",inputs: { settle_steps: 60 }. Edge directly fromcloseto thegraspedsuccess marker; the subgraph'son_error: "failed"catches any raise from earlier steps. Whether the gripper actually closed on the object is checked by thetarget_heldpostcondition checkpoint (see## Checkpoints), NOT by a re-check-and-raise node (none such exists).
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.
- yesterday Changed · +52 lines · +54 tokens per session 752d563a12cb
- 10d ago First seen · 131 lines · 85 tokens per session scan A e6f5c168f48a
grasping-direct-ik 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 2,292 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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