Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/MiaoDX/roboclawsnpx agentmods add skills/miaodx/roboclaws/scene-gaussian-map-alignmentWrote 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/miaodx/roboclaws/scene-gaussian-map-alignment)<a href="https://agentmods.dev/skills/miaodx/roboclaws/scene-gaussian-map-alignment"><img src="https://agentmods.dev/badge/skills/miaodx/roboclaws/scene-gaussian-map-alignment/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/miaodx/roboclaws/scene-gaussian-map-alignment"><img src="https://agentmods.dev/badge/skills/miaodx/roboclaws/scene-gaussian-map-alignment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00086 | $0.01448 |
| Opus 5 | $0.00043 | $0.00724 |
| Sonnet 5 | $0.00017 | $0.00290 |
| Haiku 4.5 | $0.00009 | $0.00145 |
Grade A, and why
scene-gaussian-map-alignment 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 9d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scene Gaussian Map Alignment
Use this when a bundle combines a 3D Gaussian/splat/PLY/USD/OBJ scene, a robot
map such as Nav2 YAML plus occupancy PGM, semantic anchors from
navigation_memory.json, or an Isaac/operator-console report that must label
evidence honestly.
Boundary
Keep stable, repeatable work in scripts. The skill owns the judgment that changes from scene to scene:
- Stable scripts parse headers, bounds, map metadata, semantic-memory JSON, transforms, smoke artifacts, images, and HTML reports.
- The skill decides the evidence tier, asks for missing assets, chooses which anchors are credible, names blockers, and prevents overclaiming.
- Do not hide scene-specific assumptions in a script default. If an assumption will vary with the next Gaussian scene, write it in the skill/report as an explicit decision.
Evidence Tiers
Use these labels consistently:
blocked: geometry, map files, semantic anchors, or coordinate evidence are missing.candidate: bbox fit, scale/translate, manual placement, or another heuristic alignment exists.verified: named physical/semantic anchors match across map and scene with residuals recorded.runtime_proven: Isaac or robot-view smoke renders/navigates through candidate waypoints and writes view evidence.planner_backed: a real planner/Nav2-equivalent path proof exists.
Never skip tiers in wording. A runtime smoke can prove that rendered robot views exist at candidate poses; it does not by itself prove Nav2 planner parity.
Workflow
-
Inventory every asset before aligning: Gaussian/splat/PLY files and whether they are rendered or only inspected, USD/OBJ/mesh world bounds, Nav2 YAML, occupancy grid, semantic memory, map-bundle context, anchor ids, and any segmentation/object manifest/correspondence/calibration evidence.
-
Run the deterministic tools that apply to the available assets:
python -m roboclaws.household.agibot_map_bundle \ --source-map-dir <map-root> \ --context-json <context-json> \ --output-dir assets/maps/<bundle-name> .venv-isaaclab/bin/python -m roboclaws.backends.isaaclab.b1_readiness \ --b1-root <scene-root> \ --map12-root <map-root> \ --output output/<run>/readiness.json .venv-isaaclab/bin/python -m roboclaws.backends.isaaclab.b1_navigation_smoke \ --b1-root <scene-root> \ --map12-root <map-root> \ --output-dir output/<run> \ --accept-nvidia-eula .venv-isaaclab/bin/python -m roboclaws.backends.isaaclab.b1_readiness \ --b1-root <scene-root> \ --map12-root <map-root> \ --navigation-artifact output/<run>/navigation_smoke.json \ --require-navigation-success \ --output output/<run>/readiness_with_navigation.json python -m roboclaws.backends.isaaclab.b1_navigation_report \ --run-dir output/<run>
What ships with it
2 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.
- 9d ago First seen · 151 lines · 86 tokens per session scan A 7e1431dfaf2b
scene-gaussian-map-alignment is a skill published in the GitHub repository MiaoDX/roboclaws (6 stars, last pushed 6d ago), licensed MIT. It adds 86 tokens to every session and 1,448 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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