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 agentmods add commands/mcneel/rhinoai/scenegit clone --depth 1 https://github.com/mcneel/RhinoAIWrote 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/commands/mcneel/rhinoai/scene)<a href="https://agentmods.dev/commands/mcneel/rhinoai/scene"><img src="https://agentmods.dev/badge/commands/mcneel/rhinoai/scene.svg" alt="Measured on agentmods" 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 | $0.00011 | $0.00110 |
| Opus 5 | $0.00005 | $0.00055 |
| Sonnet 5 | $0.00002 | $0.00022 |
| Haiku 4.5 | $0.00001 | $0.00011 |
Grade A, and why
scene 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- scene — 100% identical, 0 lines differ
What it actually says
Inspect the active Rhino document and give the user a concise summary:
- Call
mcp__rhino__list_objectsto see what's in the document. - Optionally call
mcp__rhino__get_selectionif the user asks about the current selection.
Report back with: object counts by type, layers in use, and anything notable (empty doc, very large object count, mixed units, etc.). Keep it short — bullets are fine.
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.
- 6d ago First seen · 11 lines · 11 tokens per session scan A 1c46a4b45207
scene is a command published in the GitHub repository mcneel/RhinoAI (280 stars, last pushed yesterday), licensed MIT. It adds 11 tokens to every session and 110 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
MIGRATE_DESIGN
Design doc for the migration tool PR. Author: Sol ([email protected]). Co-authored-by: wakesync.
awesome-chatgpt
Search awesome-ChatGPT-repositories for open-source GitHub repositories related to ChatGPT and LLMs.
commit
智能生成 Git 提交信息并提交.
create-issue
Transform feature descriptions, bug reports, or improvement ideas into well-structured GitHub issues.
pr
Handle the full workflow from current branch state to an open, CI-monitored pull request.
requirement-review
需求文档多角色评审（requirement-review）：需求文档 → 7-Agent 并行评审 → 重构高质量需求文档（Runtime 受控流程，0-7 阶段状态机）.