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-mass-report-outputgit 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-mass-report-output)<a href="https://agentmods.dev/skills/openlair/openskill/evo-mass-report-output"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-mass-report-output/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-mass-report-output"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-mass-report-output.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 | $0.00038 | $0.00399 |
| Opus 5 | $0.00019 | $0.00199 |
| Sonnet 5 | $0.00008 | $0.00080 |
| Haiku 4.5 | $0.00004 | $0.00040 |
Grade A, and why
evo-mass-report-output 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-mass-report-output
End-to-end pipeline orchestrator for mass calculation from binary STL files.
Pipeline
- Parse binary STL -> triangles with material IDs
- Find largest connected component (vertex-based adjacency, 4-decimal quantization)
- Extract Material ID from first triangle of largest component
- Look up density from material density table
- Compute volume (mm³) using signed tetrahedron method
- Convert mm³ to cm³ (divide by 1000)
- Mass = volume_cm³ × density_g/cm³
- Round to 2 decimal places
- Write JSON: {"main_part_mass": X.XX, "material_id": N}
Key Functions
run_mass_calculation_pipeline(stl_path, density_table_path, output_path)- Full pipelinewrite_mass_report_json(filepath, result)- Write JSON output
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-stl-binary-parser/scripts')
import utils as stl_parser
sys.path.insert(0, '/app/environment/skills/evo-mesh-geometry-analysis/scripts')
import utils as mesh_analysis
import importlib
importlib.reload(mesh_analysis)
triangles = stl_parser.parse_binary_stl('/root/scan_data.stl')
largest = mesh_analysis.get_largest_connected_component(triangles)
material_id = largest[0][3]
density = stl_parser.lookup_density(material_id)
vol_mm3 = mesh_analysis.compute_mesh_volume(largest)
vol_cm3 = mesh_analysis.convert_volume_mm3_to_cm3(vol_mm3)
mass = round(mesh_analysis.calculate_mass(vol_cm3, density), 2)
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 · 44 lines · 38 tokens per session scan A 513c5efa11a0
evo-mass-report-output is a skill published in the GitHub repository OpenLAIR/OpenSkill (88 stars, last pushed yesterday), licensed Apache-2.0. It adds 38 tokens to every session and 399 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.
Other skills, from other repositories
pptx-posters
Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Use when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.
paper-spine
Build, rewrite, audit, submit, revise, or transfer scholarly papers end to end, producing verified LaTeX/PDF/Word and target-specific publication packages.
paper-compile
A build workflow that turns LaTeX source files into a PDF and checks whether the paper compiles correctly. LaTeX is a text-based system commonly used for academic papers.
nsfc-ref-alignment
A read-only checker for references in NSFC LaTeX proposals. It compares citations with the bibliography and flags missing entries, field errors, and possible mismatches between claims and papers.
paper-length-gate
Deterministic artifact-backed manuscript readiness gate for meta-paper-write. Validates the workspace LaTeX artifact before compilation while leaving final page-count enforcement to compilepdf.
paper-plot-stub
Plot a results CSV (x, ybaseline, yours) as a two-line matplotlib chart and write a PDF. Demo-only.