SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.
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 benchflow-ai/skillsbench --skill mesh-analysisgit clone --depth 1 https://github.com/benchflow-ai/skillsbenchWrote 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/benchflow-ai/skillsbench/mesh-analysis)<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/mesh-analysis"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/mesh-analysis.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00043 | $0.00520 |
| Opus 5 | $0.00022 | $0.00260 |
| Sonnet 5 | $0.00009 | $0.00104 |
| Haiku 4.5 | $0.00004 | $0.00052 |
Grade A, and why
mesh-analysis 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- mesh-analysis — 100% identical, 0 lines differ
- mesh-analysis — 100% identical, 0 lines differ
- skill-079 — 95% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mesh Analysis
This skill provides the MeshAnalyzer tool for robustly processing 3D STL files. It handles Binary STL parsing and connected component analysis.
When to Use
Use this skill for:
- Geometric Analysis: Calculating volume of complex or noisy meshes.
- Noise Filtering: Isolating the largest connected component from "dirty" scan data.
- Attribute Extraction: Extracting metadata (e.g. material IDs) stored in the STL file attribute bytes.
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-analysis/scripts')
from mesh_tool import MeshAnalyzer
# Initialize with file path
analyzer = MeshAnalyzer('/path/to/your/file.stl')
# Analyze specific components
# Automatically identifies the largest component (main part)
report = analyzer.analyze_largest_component()
volume = report['main_part_volume']
mat_id = report['main_part_material_id']
print(f"Volume: {volume}")
print(f"Material ID: {mat_id}")
Calculating Mass
The tool provides the Volume and Material ID. To calculate Mass:
- Read the Material ID from the analysis report.
- Consult your provided material reference data (e.g. density tables) to find the density.
- Calculate:
Mass = Volume * Density.
Critical Note on Units:
- The Volume returned is in the same units as the STL file's coordinates (cubed).
- Do not assume millimeters or inches. Check your task instructions for the coordinate system units (e.g., if coordinates are in cm, volume is in cm³).
- If your density table uses the same unit (e.g., g/cm³ and cm³), multiply directly. No unit conversion is needed.
Critical Notes
- Binary Support: The tool automatically handles Binary STL files.
- Attribute extraction: The tool extracts the 2-byte attribute stored in the binary STL format (often used for color or material ID).
What ships with it
1 file 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.
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 · 60 lines · 43 tokens per session scan A b0c908a5e74b
mesh-analysis is a skill published in the GitHub repository benchflow-ai/skillsbench (1,748 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 43 tokens to every session and 520 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 2026-08-30.
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