docs: add generated SKILL.md discovery view

SKILL.md

@@ -0,0 +1,60 @@
+---
+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-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            # generated discovery view of an rSkill
+  schema_version: 0.1
+  rskill_id: OpenRAL/rskill-moveit-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: 2000.0}
+  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`](./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-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)
+
+```python
+from openral_rskill import rSkill
+
+skill = rSkill.from_pretrained("OpenRAL/rskill-moveit-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`](./rskill.yaml) for the authoritative, validated manifest.