skill-053

skill-053 is a skill for Claude Code, Codex from legendtkl/agentic-skill-router. It costs 35 tokens per session (438 once invoked), scanned A, original, MIT.

A tool for smoothing the surfaces of 3D mesh files, which are models made from connected polygons. It can reduce noise and unwanted irregularities in scanned or computer-generated models.

In plain words
What is it for?
Use it to visually refine 3D models, remove scan artifacts, or prepare mesh files for simulations. It supports several smoothing methods, including Laplace smoothing.
Why use it?
It helps make rough or noisy models look cleaner and prepares them for uses where surface defects could affect the result.

Skill for Claude CodeCodex

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

Good fit Use it to visually refine 3D models, remove scan artifacts, or prepare mesh files for simulations. It supports several smoothing methods, including Laplace smoothing.

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Install with agentmods
npx agentmods add skills/legendtkl/agentic-skill-router/skill-053
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 legendtkl/agentic-skill-router --skill skill-053
Clone the repo
git clone --depth 1 https://github.com/legendtkl/agentic-skill-router

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 skill-053

README.md
[![agentmods](https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-053.svg)](https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-053)
Your own site
<a href="https://agentmods.dev/skills/legendtkl/agentic-skill-router/skill-053"><img src="https://agentmods.dev/badge/skills/legendtkl/agentic-skill-router/skill-053.svg" alt="Measured on agentmods" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 438 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 $0.00035 $0.00438
Opus 5 $0.00017 $0.00219
Sonnet 5 $0.00007 $0.00088
Haiku 4.5 $0.00003 $0.00044

Measured 7d ago against content hash c96856ca5414, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

skill-053 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 7d 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.

experiments/dci-compare/skillrouter-skills/skill-053/SKILL.md · 56 lines

What it actually says

Mesh Smoothing

This skill provides the MeshSmoother tool for refining the surfaces of 3D mesh files. It applies various smoothing algorithms to improve the visual appearance and usability of the meshes in simulations.

When to Use

Use this skill for:

  1. Visual Refinement: Improving the look of 3D models for presentations or visualizations.
  2. Preprocessing for Simulation: Preparing meshes by reducing irregularities that could impact computational simulations.
  3. Artifact Removal: Eliminating unwanted noise and artifacts from 3D scans.

Usage

The tool is provided as a Python module in the scripts/ directory.

Basic Workflow

import sys
# Add skill path to sys.path
sys.path.append('/root/.claude/skills/mesh-smoothing/scripts')

from mesh_tool import MeshSmoother

# Initialize with file path
smoother = MeshSmoother('/path/to/your/file.stl')

# Smooth the mesh with default settings
smoothed_mesh = smoother.smooth()

# Save the smoothed mesh to a new file
smoother.save('/path/to/your/smoothed_file.stl')

Smoothing Techniques

The MeshSmoother supports several algorithms, including:

  • Laplace Smoothing: Smooths mesh surfaces by averaging vertex positions.
  • Taubin Smoothing: Balances surface regularization with feature preservation.

You can specify the smoothing method as follows:

smoothed_mesh = smoother.smooth(method='taubin')

Critical Notes

  • Input Format: The tool supports STL file formats.
  • Output Quality: The degree of smoothing may affect the model's fidelity. Always check the visual results after processing.
  • File Overwrite: Ensure that you save to a new file to avoid overwriting original mesh data.
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. 7d ago First seen · 56 lines · 35 tokens per session scan A c96856ca5414

Subscribe to this mod's changes

skill-053 is a skill published in the GitHub repository legendtkl/agentic-skill-router (5 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 438 once invoked, about $0.0002 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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