weldone-animation

weldone-animation is a skill for Claude Code, Codex from grasscaograss/AwesomeWeldoneSkills. It costs 189 tokens per session (2,411 once invoked), scanned A, original, Apache-2.0.

A command-line workflow that tests a welding robot's planned path from process data and a starting position, then creates Fanuc LS robot instructions. Headless means it runs without the graphical application.

In plain words
What is it for?
Use it to test single- or dual-arm plans, supply positioning matrices, generate LS files, and inspect failures or skipped crafts from the command line.
Why use it?
It lets developers check whether a welding plan works and whether external robot axes move correctly without opening the GUI.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to test single- or dual-arm plans, supply positioning matrices, generate LS files, and inspect failures or skipped crafts from the command line.

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Install with agentmods
npx agentmods add skills/grasscaograss/awesomeweldoneskills/weldone-animation
Install

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.

Any agent
npx skills add grasscaograss/AwesomeWeldoneSkills --skill weldone-animation
Clone the repo
git clone --depth 1 https://github.com/grasscaograss/AwesomeWeldoneSkills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for weldone-animation

README.md
[![agentmods](https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/weldone-animation/github.svg)](https://agentmods.dev/skills/grasscaograss/awesomeweldoneskills/weldone-animation)
Your own site
<a href="https://agentmods.dev/skills/grasscaograss/awesomeweldoneskills/weldone-animation"><img src="https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/weldone-animation/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.

agentmods 80×15 button for weldone-animation

Your own site · 80×15
<a href="https://agentmods.dev/skills/grasscaograss/awesomeweldoneskills/weldone-animation"><img src="https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/weldone-animation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 189 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,411 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00189 $0.02411
Opus 5 $0.00095 $0.01205
Sonnet 5 $0.00038 $0.00482
Haiku 4.5 $0.00019 $0.00241

Measured 10d ago against content hash 39b1c3113927, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

weldone-animation 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.

weldone-animation/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

gen-ls:PF + 粗定位 → 规划 → LS 验证

命令定位

gen-lssrc/Weldone.Cli/Commands/GenLsCommand.cs)是路径仿真模块(Pages/PathSimulation/)的 CLI 等价物:输入 PF 文件 + 粗定位位姿,跑完整生产级规划流水线并产出 Fanuc LS 脚本。不 Mock 设备、不走 FSM 执行,纯规划链路。

规划流水线(每个 craft 逐条执行):

  1. 外部轴规划 — PlanManager.ScanWeldExternalPlan(data, craftId, isDual)
  2. 焊接路径规划 — WeldRobotAppService.WeldPathPlan / WeldPathPlanDualArm
  3. 过渡规划 — PlanManager.WeldTransitionPlan / WeldTransitionDualArmPlanForCraft
  4. 逐道次生成 LS — WeldRobotAppService.GenerateLSFile / DualArmGenerateLSFile

任一步失败会打 失败/跳过 日志,不中断后续 craft。

调用方式

justfile 没有为 gen-ls 配别名,直接用 dotnet 跑 CLI 项目(工作目录 src/Weldone):

dotnet run --project src/Weldone.Cli/Weldone.Cli.csproj -- gen-ls --pf "<PF路径>" --coarse "<粗定位>" [选项]

注意:ExecuteInteractiveAsync(交互式菜单入口)被显式禁用,注释为"需要 ArmTransStateDict 支持,CLI 流程暂未适配"。只能通过命令行参数调用,不要走 just interactive 菜单

参数

参数 缩写 必填 说明
--pf -p PF 文件路径(.pf JSON,即 ProcessTransfer 序列化)
--coarse -c 粗定位矩阵,缺省=单位矩阵。三种格式见下
--user-frame 用户坐标系矩阵(同 --coarse 格式),缺省=单位矩阵
--dual 双机模式(默认单臂)
--post-mode 双机后处理模式 Async/Sync/Hybrid,默认 Async
--verify -v 生成完成后扫描 --dir 下 LS 文件,解码 GP3 外部轴点位
--dir -d --verify 的扫描/输出目录,默认 Documents\weldone

--coarse 三种格式(ParseMatrix 解析,按顺序尝试)

  1. JSON 文件路径:16 元素 float 数组,行主序 M11..M44
    [1,0,0,0, 0,1,0,0, 0,0,1,0, 100,200,300,1]
    
  2. CoarsePositionningContextDto JSON 文件:生产环境 ProductionData 目录下的 ModelBase_*.json。内部从 GeneralCoarseResults(JSON 字符串) → workpiece_results[0].model_base_result.transform_4x4 提取 m11..m44最贴近现场粗定位产物的格式
  3. inline 16 个逗号分隔浮点数:行主序
    --coarse "1,0,0,0,0,1,0,0,0,0,1,0,100,200,300,1"
    

矩阵含义:粗定位是完整 4×4 位姿矩阵(含姿态),不是单纯 XYZ 位置。规划内部会乘 UserFrame 的逆(coarseMatrix * userFrameInvert)得到工件在用户坐标系下的位姿。

典型用法

1. 单臂 + 现场粗定位文件验证规划(最常见)

dotnet run --project src/Weldone.Cli/Weldone.Cli.csproj -- gen-ls `
  --pf "D:\data\task.pf" `
  --coarse "D:\data\ModelBase_xxx.json"

Read the full file on GitHub · 137 lines

Changes

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.

  1. 10d ago First seen · 137 lines · 189 tokens per session scan A 39b1c3113927

Subscribe to this mod's changes

weldone-animation is a skill published in the GitHub repository grasscaograss/AwesomeWeldoneSkills (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 189 tokens to every session and 2,411 once invoked, about $0.0009 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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