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.
npx skills add legendtkl/agentic-skill-router --skill skill-053git clone --depth 1 https://github.com/legendtkl/agentic-skill-routerWrote 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/legendtkl/agentic-skill-router/skill-053)<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>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 | $0.00035 | $0.00438 |
| Opus 5 | $0.00017 | $0.00219 |
| Sonnet 5 | $0.00007 | $0.00088 |
| Haiku 4.5 | $0.00003 | $0.00044 |
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.
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:
- Visual Refinement: Improving the look of 3D models for presentations or visualizations.
- Preprocessing for Simulation: Preparing meshes by reducing irregularities that could impact computational simulations.
- 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.
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.
- 7d ago First seen · 56 lines · 35 tokens per session scan A c96856ca5414
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.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
general-video
Author or edit a custom HyperFrames composition when no specialized workflow fits, or when BRIEF.md sets flow: companion. Use for longer or multi-scene pieces, brand and sizzle reels, montages, static loops, static title cards, footage remixes, and freeform builds. Use motion-graphics instead for a short unnarrated…
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
diagnostic-stem-delivery
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow.
chengfeng-check-updates
An environment manager for a video-editing system. It checks whether its skills and runtime—the software needed to run them—are installed and compatible.