SKILL.md

metadata

name: rskill-moveit-joints
description: >-
  S1 ROS action skill (weightless). Capabilities: reach. Plan and execute a
  collision-free motion to a target JOINT configuration via MoveIt's MoveGroup
  (self + planning-scene collision checked). Provide one target angle per
  planning-group joint. Defaults target the Franka Panda home pose; override the
  manifest to retarget. Use when you have a joint-space goal (e.g. a policy's
  in-distribution starting pose); for a Cartesian end-effector target use
  rskill-moveit-multi-eef_pose instead. 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-multi-joints
  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-joints — 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 to a target JOINT configuration via MoveIt's MoveGroup (self + planning-scene collision checked). Provide one target angle per planning-group joint. Defaults target the Franka Panda home pose; override the manifest to retarget. Use when you have a joint-space goal (e.g. a policy's in-distribution starting pose); for a Cartesian end-effector target use rskill-moveit-multi-eef_pose instead.

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-multi-joints")
# 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.