SKILL.md

metadata

name: rskill-moveit-eef-pose
description: >-
  S1 ROS action skill (weightless). Capabilities: reach. Plan and execute a
  collision-free motion that brings the end-effector link to a target 6-DOF
  Cartesian pose (position + orientation) via MoveIt's MoveGroup (self +
  planning-scene collision checked). Use when you have a Cartesian end-effector
  goal (e.g. a pre-grasp pose); for a joint-space goal use rskill-moveit-joints,
  and to aim a camera at a point use rskill-moveit-look-at. Discovery view of an
  OpenRAL rSkill — NOT directly runnable by an agent harness; it runs via
  rSkill.from_pretrained + the robot HAL.
metadata:
  openral_rskill: true
  schema_version: 0.1
  rskill_id: OpenRAL/rskill-moveit-eef-pose
  manifest: ./rskill.yaml
  role: s1
  kind: ros_action
  embodiment_tags:
    - franka_panda
    - ur5e
    - ur10e
    - so100_follower
    - openarm
    - rizon4
    - sawyer
    - widowx
  actions:
    - reach
  chunk_size: 1
  latency_budget:
    per_chunk_ms: 2000
  license_code: Apache-2.0
  license_weights: apache-2.0
  paper_url: https://moveit.picknik.ai/

rskill-moveit-eef-pose — rSkill discovery view

Generated view, not a hand-written skill. This SKILL.md is a discovery-only mirror of rskill.yaml, produced by tools/generate_rskill_skillmd.py. It lets tools that read the standard agent-skill format find and reason about this OpenRAL rSkill. The rskill.yaml manifest is the single source of truth (CLAUDE.md §1.3). Do not edit by hand — edit the manifest and regenerate.

What it is

An OpenRAL ROS action skill (weightless) (role: s1, kind: ros_action). Plan and execute a collision-free motion that brings the end-effector link to a target 6-DOF Cartesian pose (position + orientation) via MoveIt's MoveGroup (self + planning-scene collision checked). Use when you have a Cartesian end-effector goal (e.g. a pre-grasp pose); for a joint-space goal use rskill-moveit-joints, and to aim a camera at a point use rskill-moveit-look-at.

Capabilities

• Verbs: reach
• Embodiments: franka_panda · ur5e · ur10e · so100_follower · openarm · rizon4 · sawyer · widowx

Why this is discovery-only

An agent skill is natural-language instructions loaded into an LLM's context. An rSkill is an executable artifact: it carries a typed capability/embodiment contract a runtime, and a license/provenance gate — none of which fit in freeform markdown. So an agent can use this view to select the right skill, but cannot execute it by loading this file. Execution always goes through the OpenRAL loader and the robot HAL.

License

• Code: Apache-2.0. This is a weightless rSkill (the manifest is the artifact).

How to actually run it (not via an agent harness)

from openral_rskill import rSkill

skill = rSkill.from_pretrained("OpenRAL/rskill-moveit-eef-pose")
# the loader validates embodiment / sensors / runtime / quantization against the target
# RobotDescription and enforces the weight-license gate before any weights load.

See rskill.yaml for the authoritative, validated manifest.