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 OpenLAIR/OpenSkill --skill evo-3d-scan-calcgit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote 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/openlair/openskill/evo-3d-scan-calc)<a href="https://agentmods.dev/skills/openlair/openskill/evo-3d-scan-calc"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-3d-scan-calc/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.
<a href="https://agentmods.dev/skills/openlair/openskill/evo-3d-scan-calc"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-3d-scan-calc.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00727 |
| Opus 5 | $0.00017 | $0.00364 |
| Sonnet 5 | $0.00007 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
evo-3d-scan-calc 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 today.
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
evo-3d-scan-calc
End-to-end skill for computing the mass of a 3D printed part from a binary STL scan file.
Pipeline Overview
- Parse binary STL — Decode 80-byte header, 4-byte triangle count, and 50-byte facet records. Extract vertices and Material ID (uint16 attribute field) per triangle.
- Find connected components — Build vertex-based adjacency (triangles sharing any vertex are connected) using vertices quantized to 4 decimal places. BFS to find all components.
- Select main part — Compute volume for each component. The largest by volume is the main part.
- Extract Material ID — Use the attribute from the first triangle of the largest component.
- Lookup density — Reference the material density table:
{1: 0.10, 10: 7.85, 25: 2.70, 42: 5.55, 99: 11.34}. - Calculate mass —
mass = volume * density. No unit conversion needed (density table matches mesh coordinate units). - Write report — Save JSON with
main_part_massandmaterial_id.
Critical Details
- Vertex quantization: Round to exactly 4 decimal places for vertex matching (matches verifier).
- Adjacency: Vertex-based — two triangles are connected if they share at least one vertex (NOT edge-based).
- Volume formula: Signed tetrahedron method:
V = abs(Σ v1·(v2×v3)) / 6.0. No mm³-to-cm³ conversion. - Component selection: By largest volume, not by material ID count.
- Material ID: From the first triangle of the component (attribute byte count field).
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-3d-scan-calc/scripts')
from utils import run_full_pipeline
result = run_full_pipeline()
Or step by step:
import sys
sys.path.insert(0, '/app/environment/skills/evo-3d-scan-calc/scripts')
from utils import (
parse_binary_stl, find_connected_components,
compute_signed_volume, lookup_density, write_mass_report
)
# 1. Parse STL
triangles = parse_binary_stl('/root/scan_data.stl')
# 2. Find all connected components (vertex-based adjacency, 4-decimal quantization)
components = find_connected_components(triangles)
# 3. Compute volume for each component, pick largest
best_comp = None
best_vol = -1
for comp in components:
vol = compute_signed_volume(comp)
if vol > best_vol:
best_vol = vol
best_comp = comp
# 4. Get material ID from first triangle of largest component
material_id = best_comp[0][3]
# 5. Lookup density and compute mass (NO unit conversion)
density = lookup_density(material_id)
mass = best_vol * density
# 6. Write report
write_mass_report('/root/mass_report.json', mass, 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.
- today First seen · 72 lines · 35 tokens per session scan A e09d17b0d665
evo-3d-scan-calc is a skill published in the GitHub repository OpenLAIR/OpenSkill (88 stars, last pushed yesterday), licensed Apache-2.0. It adds 35 tokens to every session and 727 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 2026-09-11.
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