weldone-project-logs

weldone-project-logs is a skill for Claude Code, Codex from grasscaograss/AwesomeWeldoneSkills. It costs 143 tokens per session (1,518 once invoked), scanned A, original, Apache-2.0.

A diagnostic skill that reads Weldone welding software’s project logs and configuration files from the current Windows user’s application data folder.

In plain words
What is it for?
Use it to inspect recent Weldone logs, identify the active project, and check device, robot, workspace, and production settings when a project such as KukaTest or JuLi has problems.
Why use it?
It helps find runtime errors and verify which project, devices, and welding-plan settings are active without guessing file locations.

Skill for Claude CodeCodex

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

Good fit Use it to inspect recent Weldone logs, identify the active project, and check device, robot, workspace, and production settings when a project such as KukaTest or JuLi has problems.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/grasscaograss/awesomeweldoneskills/weldone-project-logs
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-project-logs
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-project-logs

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/grasscaograss/awesomeweldoneskills/weldone-project-logs"><img src="https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/weldone-project-logs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 143 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,518 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 $0.00143 $0.01518
Opus 5 $0.00072 $0.00759
Sonnet 5 $0.00029 $0.00304
Haiku 4.5 $0.00014 $0.00152

Measured 12d ago against content hash 622ca0ab1f0c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

weldone-project-logs 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/resolve_project.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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-project-logs/SKILL.md · 92 lines

How it starts

The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Weldone 项目日志与配置读取

Overview

定位并读取 Weldone 焊接软件在本机的运行日志(Serilog 文本格式)和项目配置 JSON(DeviceSetting、RobotPlanSetting、WorkspaceSetting 等),用于排障、检查运行状态、核对设备/规划参数。所有路径基于 %APPDATA% 环境变量动态解析,不依赖任何写死的用户名。

路径解析规则(核心)

Weldone 的配置与日志位置由三层目录构成:

%APPDATA%\Roboticplus\Weldone\1.0.x\          ← 配置根目录(固定)
├── ProjectConfig.json                         ← 读 ProjectFolder 字段
├── DeviceSetting.json                         ← 全局设备清单
└── <ProjectFolder>\                           ← 当前项目子目录(如 KukaTest、JuLi)
    ├── *.json                                 ← 项目级配置(见 references)
    ├── Logs\logs-YYYYMMDD[_HHMMSS].log        ← 运行日志(本 skill 的主要目标)
    ├── Debug\                                 ← 规划中间结果 JSON
    └── ProductionData\                        ← 生产数据快照

关键原则

  • 配置根目录永远是 %APPDATA%\Roboticplus\Weldone\1.0.x,其中 %APPDATA% 在 Windows 等于 C:\Users\<当前用户>\AppData\Roaming禁止在任何输出或脚本里写死 mini-pc 之类的用户名。
  • 哪个项目是"当前项目"由 ProjectConfig.jsonProjectFolder 字段决定,不要假设;总是先读它。

执行流程

1. 定位路径与日志清单

优先运行脚本(确定性、token 高效):

python "<skill>/scripts/resolve_project.py" --list

输出:配置根目录、当前项目名、项目目录、日志目录,以及日志文件按修改时间倒序的清单(含文件大小、修改时间,并对 0KB 文件标注提示)。

需要看其它项目时加 --project <名字>

python "<skill>/scripts/resolve_project.py" --list --project JuLi

若手头没有可用的 Python,按上述路径规则用 Bash + $APPDATA/Read 工具自行定位(Git Bash 下用 "$APPDATA/Roboticplus/Weldone/1.0.x")。

2. 读取日志

日志在 <项目目录>/Logs/ 下。读取策略:

  • 定位最近一次运行:清单里修改时间最新、且带 _HHMMSS 后缀的文件通常就是最近一次启动。无后缀的(如 logs-20260417.log)是按日滚动的旧格式。
  • 目标式检索优先:大文件(数百 KB ~ 数 MB)不要整读。用 Grep 工具按级别或关键词过滤:
    • 按级别:Grep pattern \[(ERR|FTL|WRN)\] —— 排障时先抓异常和警告。
    • 按异常关键词:报错堆栈里的类名/方法名/异常类型。
    • 按时间窗口:先 Grep 出该次启动的时间范围,再读对应行。
  • 中小文件可直接用 Read 工具读取(默认 2000 行)。
  • 日志行格式:2026-06-29 11:31:48.333 +08:00 [INF] 消息,级别缩写见 references。

3. 读取配置 JSON

项目目录与配置根目录下的 *.json 都可读。常见用途:

  • 核对设备连接(DeviceSetting.jsonDeviceInfos[].ConnectInfo.IP/Port
  • 核对机器人 TCP / 用户坐标系(RobotPlanSetting.jsonTcpSettingsUserFrame
  • 核对工位布局(WorkspaceSetting.json
  • 核对当前激活项目(ProjectConfig.json

Read the full file on GitHub · 92 lines

Files

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.

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. 12d ago First seen · 92 lines · 143 tokens per session scan A 622ca0ab1f0c

Subscribe to this mod's changes

weldone-project-logs is a skill published in the GitHub repository grasscaograss/AwesomeWeldoneSkills (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 143 tokens to every session and 1,518 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.

Related

Other skills, from other repositories

debug-optimize-lcp

Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…

ChromeDevTools/chrome-devtools-mcp · 99 tokens

systematic-debugging

Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.

open-metadata/OpenMetadata · 37 tokens

diagnose

Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.

emdash-cms/emdash · 43 tokens

repro-admin

Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.

emdash-cms/emdash · 48 tokens

log-error-digest

Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…

zebbern/claude-code-guide · 71 tokens

byted-util-volcengine-detect-retry

An orchestration workflow for Volcengine Cloud Detect, a service that checks websites or network endpoints from test locations.

bytedance/agentkit-samples · 101 tokens