Borrowing it
Nothing to install: this file belongs to AmemiyaLai/grasshopper-mcp-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AmemiyaLai/grasshopper-mcp-workflow/main/.claude/skills/grasshopper-workflow/SKILL.mdgit clone --depth 1 https://github.com/AmemiyaLai/grasshopper-mcp-workflowWrote 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/amemiyalai/grasshopper-mcp-workflow/grasshopper-workflow)<a href="https://agentmods.dev/skills/amemiyalai/grasshopper-mcp-workflow/grasshopper-workflow"><img src="https://agentmods.dev/badge/skills/amemiyalai/grasshopper-mcp-workflow/grasshopper-workflow/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/amemiyalai/grasshopper-mcp-workflow/grasshopper-workflow"><img src="https://agentmods.dev/badge/skills/amemiyalai/grasshopper-mcp-workflow/grasshopper-workflow.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 | $0.00132 | $0.01766 |
| Opus 5 | $0.00066 | $0.00883 |
| Sonnet 5 | $0.00026 | $0.00353 |
| Haiku 4.5 | $0.00013 | $0.00177 |
Grade A, and why
grasshopper-workflow 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 10d 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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grasshopper Workflow Skill
概述
此技能提供完整的 Grasshopper 參數化建模工作流程，包括組件管理、連接管理、參數設置、群組管理和工作流程執行。整合了從需求分析到最終執行的完整流程。
核心功能
1. 組件管理
- 創建、查詢、刪除組件
- 並行創建多個組件
- 組件 ID 映射管理
- 組件 GUID 查詢
2. 連接管理
- 建立組件之間的連接
- 並行連接多個組件
- 連接錯誤檢查和修正
- 文檔錯誤診斷
3. 參數設置
- 設置 Number Slider 屬性
- 設置 Vector XYZ 組件
- 批量參數設置
- 自動範圍確定
4. 群組管理
- 創建組件群組
- 批量創建群組
- 自定義群組顏色和名稱
5. 工作流程執行
- 解析 MMD 文件（component_info.mmd, part_info.mmd）
- 生成 placement_info.json
- 執行完整建模流程
- 自動化腳本執行
快速開始
基本使用
from scripts.client import GrasshopperClient
from scripts.component_manager import ComponentManager
from scripts.connection_manager import ConnectionManager
from scripts.parameter_setter import ParameterSetter
from scripts.group_manager import GroupManager
# 創建客戶端
client = GrasshopperClient(host="localhost", port=8080)
# 創建組件管理器
comp_mgr = ComponentManager(client)
# 創建組件
component_id = comp_mgr.add_component(
guid="e2bb9b8d-0d80-44e7-aa2d-2e446f5c61da",
x=100,
y=200,
component_id="SLIDER_WIDTH"
)
完整工作流程
from scripts.parser_utils import MMDParser, JSONGenerator
from scripts.placement_executor import PlacementExecutor
# 1. 解析 MMD 文件
parser = MMDParser()
components, connections = parser.parse_component_info_mmd("component_info.mmd")
# 2. 生成 placement_info.json
generator = JSONGenerator()
placement_info = generator.generate_placement_info(components, connections)
generator.save_placement_info(placement_info, "placement_info.json")
# 3. 執行
executor = PlacementExecutor()
result = executor.execute_placement_info("placement_info.json")
工作流程步驟
Grasshopper 建模工作流程包含 6 個主要步驟：
- 釐清設計需求與規格 - 參見 references/workflow_steps.md
- 拆分幾何物件創建 part_info.mmd - 參見 references/workflow_steps.md
- 規劃電池實際連接圖 component_info.mmd - 參見 references/workflow_steps.md
- 找出所需組件 GUID 並規劃位置 - 參見 references/workflow_steps.md
- 生成執行序列檔案 placement_info.json - 參見 references/workflow_steps.md
- 清理 GH_WIP 檔案 - 參見 references/workflow_steps.md
What ships with it
15 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.
- references/api_reference.md 11 KB
- references/cli_usage.md 8.6 KB
- references/tool_guide.md 15 KB
- references/workflow_steps.md 14 KB
- scripts/cli.py 15 KB runs code
- scripts/client.py 3.4 KB runs code
- scripts/component_manager.py 8.5 KB runs code
- scripts/connection_manager.py 7.4 KB runs code
- scripts/example_usage.py 6.1 KB runs code
- scripts/gh_cli.py 417 B runs code
- scripts/group_manager.py 4.6 KB runs code
- scripts/parameter_setter.py 7.7 KB runs code
- scripts/parser_utils.py 20 KB runs code
- scripts/placement_executor.py 6.1 KB runs code
- scripts/utils.py 6.3 KB runs code
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.
- 10d ago First seen · 169 lines · 132 tokens per session scan A 621ff368617c
grasshopper-workflow is a skill published in the GitHub repository AmemiyaLai/grasshopper-mcp-workflow (4 stars, last pushed 4d ago), licensed MIT. It adds 132 tokens to every session and 1,766 once invoked, about $0.0007 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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