Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add graph-robots/open-robot-skills --skill pi05-liberogit clone --depth 1 https://github.com/graph-robots/open-robot-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/graph-robots/open-robot-skills/pi05-libero)<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/pi05-libero"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/pi05-libero/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/graph-robots/open-robot-skills/pi05-libero"><img src="https://agentmods.dev/badge/skills/graph-robots/open-robot-skills/pi05-libero.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00183 | $0.01186 |
| Opus 5.5 | $0.00073 | $0.00474 |
| Sonnet 5.5 | $0.00037 | $0.00237 |
| Haiku 4.5 | $0.00018 | $0.00119 |
Grade A, and why
pi05-libero scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pi05-libero
Closed-loop VLA-policy skill backed by one model checkpoint: openpi's
π0.5 LIBERO checkpoint (pi05_libero). The skill is the model — it owns
its serving preset (pi05-libero), so a policy node names this skill, not a
free-floating policy_id. The closed-loop replan/execute/terminate body and
the load-bearing LIBERO observation encoding live in
gap.runtime.policy.run_policy_loop; the websocket client is resolved (and
cached per preset) through the executor's PolicyExecutor.
Capability
- Embodiment: Franka Panda (LIBERO/robosuite), OSC_POSE delta action
space
[Δx, Δy, Δz, Δrx, Δry, Δrz, gripper]. No embodiment translation happens in the loop — the checkpoint's native action space is forwarded tosim.apply_policy_action. - Tasks: the LIBERO pick-and-place distribution — pick a tabletop rigid object, optionally place/drop it in a container. Works best steered: perceive the target and hover the end-effector above it (preserving the current rotation) before handing over, so the policy starts in-distribution.
- Not for: deformables / cloth folding, articulated objects, non-LIBERO embodiments, or tasks the checkpoint never saw. If the task is outside this envelope, pick a different skill or report a missing capability — do not delegate it here and hope.
Serving
The bundle ships its own server.py (vendored from openpi scripts/serve_policy.py)
and declares openpi as a git dep in its own pyproject.toml — so this
bundle is self-contained: no $GAP_OPENPI_DIR clone, no shared venv.
First-run setup is gap skills install pi05-libero, which uv syncs the
bundle's .venv/ with all model deps. The launcher then spawns the server
via uv run --project policies/pi05-libero -- python server.py ... (so the
bundle's own venv activates automatically) and downloads the checkpoint from
s3://openpi-assets/checkpoints/pi05_libero on first run.
Run it yourself with gap policy serve pi05-libero. A policies: config
entry named pi05-libero overrides the recipe (e.g. an external url:).
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 89 lines · 183 tokens per session scan A c59136b82f83
pi05-libero is a skill published in the GitHub repository graph-robots/open-robot-skills (58 stars, last pushed 25d ago), licensed Apache-2.0. It adds 183 tokens to every session and 1,186 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
gap
Program robots with GaP (graph-as-policy) — compile natural-language tasks into typed, verified robot skill graphs and run them on simulators or real robots. Use when the user mentions GaP or graph-as-policy, robot manipulation, robot skills, robot tools or capabilities, skill registries, open-robot-skills, LIBERO or…
srdf
MoveIt2 SRDF authoring, validation, and planning-semantics workflow. Use when creating, editing, inspecting, or validating .srdf files, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-paired planning semantics, or SRDF handoff for live review. Use the URDF…
urdf
URDF robot description authoring and validation. Use when creating, editing, inspecting, validating, or debugging .urdf files, robot links, joints, limits, inertials, visual/collision geometry, mesh references, frame conventions, or robot-description artifacts. Use the SRDF skill for MoveIt2 semantic groups and…
step-parts
Find, evaluate, and download common purchasable CAD parts from step.parts, including named off-the-shelf actuators, servos, motors, electronics boards, connectors, screws, bolts, nuts, washers, bearings, standoffs, and other catalog components. Use when Codex needs to search the hosted step.parts catalog before…
gcode
Slice 3D models into printer-ready G-code with OrcaSlicer, the open-source slicer with built-in profiles for most FDM printers (Prusa, Bambu Lab, Creality, Voron and more). Use when the user wants an .stl, .3mf or .obj model sliced for their printer, as a sliced .gcode.3mf or plain .gcode, headless with OrcaSlicer's…
sendcutsend
Review DXF and STEP/STP uploads for SendCutSend.com orders using its ordering guide, catalog, and specs. Use only for SendCutSend.com preflight reports covering upload readiness, selected material/SKU/thickness/service availability, and service-specific checks for laser cutting, CNC routing, bending, tapping…