weldone-hybrid-seam-replay-debug

weldone-hybrid-seam-replay-debug is a skill for Claude Code, Codex from grasscaograss/AwesomeWeldoneSkills. It costs 57 tokens per session (1,101 once invoked), scanned A, original, Apache-2.0.

A debugging guide for replaying and diagnosing Weldone hybrid-weld reconstruction packages, including laser-point fitting and arc geometry.

In plain words
What is it for?
Use it with single- or dual-arm hybrid replay packages to reproduce failures, inspect fitting diagnostics, and save results without overwriting the original package.
Why use it?
It provides a focused way to tell whether a reconstruction failure comes from point-cloud quality, fitting thresholds, geometry, or the replay-saving process.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; mentions AGENTS.md.

Good fit Use it with single- or dual-arm hybrid replay packages to reproduce failures, inspect fitting diagnostics, and save results without overwriting the original package.

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Install with agentmods
npx agentmods add skills/grasscaograss/awesomeweldoneskills/weldone-hybrid-seam-replay-debug
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-hybrid-seam-replay-debug
Clone the repo
git clone --depth 1 https://github.com/grasscaograss/AwesomeWeldoneSkills

Made for: Claude Code, Codex.

Its marketplace also offers this one on its own, as the plugin weldone-hybrid-seam-replay-debug/plugin install weldone-hybrid-seam-replay-debug after adding the marketplace above.

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-hybrid-seam-replay-debug

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/grasscaograss/awesomeweldoneskills/weldone-hybrid-seam-replay-debug"><img src="https://agentmods.dev/badge/skills/grasscaograss/awesomeweldoneskills/weldone-hybrid-seam-replay-debug.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,101 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 $0.00057 $0.01101
Opus 5 $0.00028 $0.00550
Sonnet 5 $0.00011 $0.00220
Haiku 4.5 $0.00006 $0.00110

Measured 12d ago against content hash 2420c85ec2e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

weldone-hybrid-seam-replay-debug 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/summarize_replay_arc_diagnostics.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-hybrid-seam-replay-debug/SKILL.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Weldone Hybrid Seam Replay Debug

Overview

定位 Weldone 混合焊缝重构问题时,优先围绕 replay 包复现、RANSAC 拟合质量、Arc 弱诊断和重构几何连续性推进。目标是用最少代码改动判断是点云质量问题、阈值策略问题、端点/相切几何问题,还是 replay 包/CLI 保存链路问题。

Trigger Scenarios

Use this skill when the user mentions any of these:

  • SingleHybridReconstructionReplayPackage.json or ReconstructionReplayPackage.json.
  • replay-single-hybrid, replay-dualarm-hybrid, or "新的 replay 包能不能存下来".
  • 单机混合焊缝、双机混合焊缝、HybridSeam、LaserPoint RANSAC、Arc 拟合失败。
  • 半径偏差、圆心偏差、短弧 3 点、弦高、相切关系、端头锚点、未扫描 arc 对齐。
  • Logs containing HybridRansacFitException, LaserPoint Arc RANSAC, RadiusDeviation, CenterDeviation, MaxResidual, or InlierRatio.

Fast Workflow

  1. Read AGENTS.md and CLAUDE.md in the Weldone repo before changing code.
  2. Identify package type:
    • SingleHybridReconstructionReplayPackage.json -> run just replay-single-hybrid "INPUT_PATH" "OUTPUT_PATH".
    • ReconstructionReplayPackage.json -> run just replay-dualarm-hybrid "INPUT_PATH" "OUTPUT_PATH".
  3. Never overwrite the original replay package. Always write a timestamped output beside it or into a temp/debug folder.
  4. After CLI replay, inspect:
    • FailureExceptionType / FailureMessage.
    • LineFitDiagnostics, ArcFitDiagnostics, CommonTangentDiagnostics.
    • Reconstructed segment count, endpoint anchor error, tangent continuity logs.
  5. Use scripts/summarize_replay_arc_diagnostics.py REPLAY_JSON_OR_DIRECTORY to summarize Arc diagnostics quickly.
  6. If CLI execution modifies src/Weldone.Cli/Logs/logs.txt, restore it unless the user explicitly wants log changes committed.
  7. Add or update focused tests before finalizing:
    • HybridSeamSegmentFitterTests for domain fitting behavior.
    • HybridSinglePointReconstructionTests for single-machine application behavior when relevant.
    • Replay CLI verification with a field package when available.

Arc Threshold Policy

Treat Arc RANSAC hard failures as point-cloud quality failures only:

  • InlierRatio at least 0.6.
  • RmsResidual at most 1.0mm.
  • MaxResidual at most 2.0mm.

Read the full file on GitHub · 78 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 · 78 lines · 57 tokens per session scan A 2420c85ec2e8

Subscribe to this mod's changes

weldone-hybrid-seam-replay-debug is a skill published in the GitHub repository grasscaograss/AwesomeWeldoneSkills (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 57 tokens to every session and 1,101 once invoked, about $0.0003 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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