rskill-playbook-stage_for_manipulation
A kind: playbook rSkill: a symbolic S2 decision procedure the
Reasoner reads, not a neural policy. It carries no weights β the authored
PLAYBOOK.md is its runtime.
What this skill does
Moves the robot into a manipulation skill's declared pre-grasp / starting_pose
and verifies it before the manipulation policy runs, reducing grasp failures
caused by a bad initial pose. It reads the target skill's starting_pose,
optionally navigates a mobile base so the target sits inside the arm's workspace,
drives the arm to the pre-grasp through the collision-aware MoveGroup approach
skill, confirms the pose with query_scene, and only then hands
control back. Concrete walkthrough: the black-bowl example in
PLAYBOOK.md.
How it works
This playbook is content, not code. When installed, the reasoner injects
PLAYBOOK.md into its system prompt and follows the SOP, composing tools it
already has (resolve_place, execute_rskill, query_scene, memory_write). It
is role: s2 and is never dispatched through ExecuteSkill. Every motion it
triggers is an execute_rskill β Action chunk β C++ safety kernel β the playbook
holds no actuation authority (CLAUDE.md Β§1.1).
Observation β action contract
None. A playbook emits no Action chunks and requires no actuators
(actuators_required: [], chunk_size: 1). Its "output" is the sequence of
tool calls the reasoner makes while following the SOP, bounded by
playbook.max_steps.
How it was authored / Upstream provenance
N/A β a playbook is hand-authored, not trained: it has no weights and no
upstream model. Its provenance is the authoring decision record
(also linked via paper_url). To change behaviour, edit PLAYBOOK.md and bump
version.
Supported robots
Embodiment-agnostic β declares the explicit wildcard embodiment_tags: ["any"]
(never an empty list). Gated by capabilities_required
(has_vision: true β a real RobotCapabilities flag): the loader filters it out
on robots without a camera (the pre-grasp verification needs vision). Arm motion /
navigation are gated at runtime by the composed tools, not by this playbook's
flags.
Sensors required
None directly. The tools it composes declare their own sensor needs.
Manifest summary
kind: playbook,role: s2,actions: [plan],chunk_size: 1.playbook.trigger: a manipulation skill declares a starting_pose / pre-grasp the robot is not currently in.playbook.done_predicate: the robot is in the skill's declared pre-grasp / starting pose, verified, and ready to dispatch the manipulation.playbook.max_steps: 8.
Quick start
from openral_core.schemas import RSkillManifest
m = RSkillManifest.from_yaml("rskills/stage-for-manipulation/rskill.yaml")
assert m.kind == "playbook" and m.playbook is not None
print(m.playbook.trigger)
Reproduction
Packaging-only: the manifest + SOP are validated by
tests/unit/test_playbook_rskill_manifest.py. There is no benchmark number to
reproduce; the playbook's behaviour is exercised by the reasoner integration
tests in later phases.
Evaluation
N/A β no eval/*.json; a playbook produces no benchmarkable policy output.
License
- Code / content: Apache-2.0.
- Weights: none.
See also
PLAYBOOK.mdβ the decision procedure itself.