chore: publish rSkill OpenRAL/rskill-act-aloha v0.1.0

README.md

@@ -58,7 +58,7 @@ wrist or third-person view.
 
 | Field | Value |
 | --- | --- |
-| `name` | `AdrianLlopart/rskill-act-aloha` |
+| `name` | `OpenRAL/rskill-act-aloha` |
 | `version` | `0.1.0` |
 | `license` | `mit` |
 | `role` | `s1` |
@@ -76,13 +76,13 @@ Full schema: `openral_core.RSkillManifest` —
 ## Reproduction
 
 ```bash
-git clone https://github.com/AdrianLlopart/openral && cd OpenRAL
+git clone https://github.com/OpenRAL/openral && cd OpenRAL
 just bootstrap && uv sync --all-packages --group sim
 
 # End-to-end via the canonical SimEnvironment config:
 just sim-act-aloha
 # which runs:
-#     ral sim run --config examples/sim/act_aloha_transfer_cube.yaml --save-video
+#     openral sim run --config scenes/benchmarks/act_aloha_transfer_cube.yaml --save-video
 
 # Sim test (real gym-aloha MuJoCo with contact dynamics):
 uv run pytest tests/sim/test_aloha_bimanual_act_aloha.py -v -m sim
@@ -97,5 +97,5 @@ upstream weights. Commercial use is allowed
 ## See also
 
 - [`robots/aloha_bimanual/README.md`](../../robots/aloha_bimanual/README.md) — RobotDescription manifest.
-- [`examples/sim/act_aloha_transfer_cube.yaml`](../../examples/sim/act_aloha_transfer_cube.yaml) — paired SimEnvironment config.
+- [`scenes/benchmarks/act_aloha_transfer_cube.yaml`](../../scenes/benchmarks/act_aloha_transfer_cube.yaml) — paired SimEnvironment config.
 - [`docs/reference/vla_compatibility.md`](../../docs/reference/vla_compatibility.md) — VLA × Robot × Sim matrix.

eval/README.md

@@ -3,7 +3,7 @@
 `aloha_transfer_cube.json` is the ALOHA bimanual cube-transfer benchmark
 result block for this rSkill. Validated against
 [`openral_core.RSkillEvalResult`](../../../docs/reference/schemas/RSkillEvalResult.json)
-at load time by the `rSkill` loader and surfaced by `ral benchmark report`.
+at load time by the `rSkill` loader and surfaced by `openral benchmark report`.
 
 | Field | Value |
 | --- | --- |

eval/aloha_transfer_cube.json

@@ -1,13 +1,13 @@
 {
-  "schema_version": "1",
+  "schema_version": "0.1",
   "source": {
     "paper": "https://arxiv.org/abs/2304.13705",
     "arxiv": "https://arxiv.org/abs/2304.13705",
     "model_variant": "act",
-    "evaluated_by": "OpenRAL:ral benchmark run",
+    "evaluated_by": "OpenRAL:openral benchmark run",
     "reproduced_locally": true,
     "reproduction_planned": null,
-    "reproduction_cli": "ral benchmark run --suite aloha_transfer_cube --rskill rskill://act-aloha",
+    "reproduction_cli": "openral benchmark run --suite aloha_transfer_cube --rskill rskill://act-aloha",
     "table": null,
     "status": "reproduced"
   },

rskill.yaml

@@ -1,23 +1,32 @@
 # rSkill manifest — OpenRAL packaging format V1 (CLAUDE.md §6.4)
 # Wraps: lerobot/act_aloha_sim_transfer_cube_human (MIT)
 # Paper: Zhao et al., 2023 — Action Chunking Transformer.
-
-schema_version: "1"
-
-name: "AdrianLlopart/rskill-act-aloha"
+#
+# LEGACY PROCESSOR PATH: this checkpoint pre-dates lerobot's
+# PolicyProcessorPipeline migration and ships its norm stats inside
+# model.safetensors. The schema's processors block is therefore omitted;
+# the ACT adapter dispatches on manifest.processors is None and falls
+# back to the snapshot_download + _try_load_act_norm_stats path. Migrating
+# to per-file URIs would require re-publishing the upstream checkpoint
+# and is tracked as a follow-up.
+
+# ── Identity ───────────────────────────────────────────────────────────────
+schema_version: "0.1"
+name: "OpenRAL/rskill-act-aloha"
 version: "0.1.0"
 license: "mit"
 role: "s1"
+kind: "vla"  # ADR-00XX: rSkill kind discriminator. "vla" = learnable Vision-Language-Action policy.
 
+# ── Policy identity ────────────────────────────────────────────────────────
 model_family: "act"
 
+# ── Compatibility contract ─────────────────────────────────────────────────
 # Bimanual ALOHA (2 × 7-DoF arms = 14-DoF action space). Used by
 # tests/sim/test_aloha_bimanual_act_aloha.py (gym-aloha MuJoCo).
 embodiment_tags:
   - "aloha"
 
-capabilities_required: {}
-
 # ACT for ALOHA cube-transfer ships with a single top-down 480×640 RGB stream.
 sensors_required:
   - modality: "rgb"
@@ -30,17 +39,25 @@ sensors_required:
 # robots/aloha_bimanual/robot.yaml.
 actuators_required:
   - kind: "joint_position"
+    control_mode_semantics:
+      mode: "absolute"
 
+# ── Runtime / weights ──────────────────────────────────────────────────────
 runtime: "pytorch"
-
 quantization:
   dtype: "fp32"
   backend: "pytorch"
-
 weights_uri: "hf://lerobot/act_aloha_sim_transfer_cube_human"
 
-chunk_size: 100
+# ── Preprocessing (all knobs needed to interpret IO) ───────────────────────
+# processors omitted — legacy path; norm stats live inside model.safetensors.
+# ACT manages its own preprocessing / state contract inside the lerobot
+# ACTPolicy so nothing else needs to move.
 
+# ── Execution semantics ────────────────────────────────────────────────────
+chunk_size: 100
+# n_action_steps omitted — ACT default is 1 (per-step re-inference +
+# temporal ensembling, paper-faithful).
 latency_budget:
   # Reference-host measurement (RTX 4070 Laptop, CUDA 12.8, PyTorch 2.10)
   # of the warm full-chunk inference is 16 ms; bf16 autocast is ~12 ms.
@@ -48,20 +65,13 @@ latency_budget:
   # "tolerance_pct=100 → 2× ceiling" pattern (giving a 50 ms test ceiling,
   # matching the previous _WARM_CHUNK_CEILING_S = 0.050).
   per_chunk_ms: 25.0
-  warmup_ms: 5000.0
-  load_ms: 10000.0
-
-fallback_skill_id: null
 
+# ── Provenance ─────────────────────────────────────────────────────────────
 # Headline success rate from skills/act-aloha/eval/aloha_transfer_cube.json
-# (50 episodes via `ral benchmark run`).
+# (50 episodes via `openral benchmark run`).
 benchmarks:
   aloha_transfer_cube: 0.82
 
-# Policy-class identity; ACT manages its own preprocessing / state
-# contract inside the lerobot ACTPolicy so nothing else needs to move.
-policy_id: "act"
-
 paper_url: "https://arxiv.org/abs/2304.13705"
 source_repo: "hf://lerobot/act_aloha_sim_transfer_cube_human"
 
@@ -72,3 +82,24 @@ description: >
   PolicyProcessorPipeline migration and ships without normalisation
   buffers — see tests/sim/test_aloha_bimanual_act_aloha.py for the
   resulting numerical-contract caveats.
+
+# ADR-0022 — action vocabulary surfaced to the reasoner LLM tool
+# palette so it can pick this skill by what it does (action verb +
+# object + scene), not just by its slug.
+actions:
+  - "transfer"
+  - "pick"
+  - "place"
+objects:
+  - "cube"
+scenes:
+  - "tabletop"
+
+# ADR-0019 — per-checkpoint action contract (consumed by the dataset bridge
+# to bind the LeRobot v3 `action` feature shape).
+action_contract:
+  dim: 14
+
+# ADR-0019 — per-checkpoint state contract.
+state_contract:
+  dim: 14