Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/tdimino/claude-code-minoannpx agentmods add skills/tdimino/claude-code-minoan/meshyWrote 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/tdimino/claude-code-minoan/meshy)<a href="https://agentmods.dev/skills/tdimino/claude-code-minoan/meshy"><img src="https://agentmods.dev/badge/skills/tdimino/claude-code-minoan/meshy/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/tdimino/claude-code-minoan/meshy"><img src="https://agentmods.dev/badge/skills/tdimino/claude-code-minoan/meshy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 32 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Agent Snooping · line 117 Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
- medium MCP Rug Pull · line 211 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium Excessive Agency · line 236 Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
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 | $0.00126 | $0.02576 |
| Opus 5 | $0.00063 | $0.01288 |
| Sonnet 5 | $0.00025 | $0.00515 |
| Haiku 4.5 | $0.00013 | $0.00258 |
Grade B, and why
meshy scanned grade B with 1 finding 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 10d 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
All three accept local file paths (auto base64-encoded) or URLs. Run any script with `--help` for flags. How it starts
The opening of the file, as written. The whole thing — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
3D Model Generation (Multi-Provider)
Generate 3D models from text prompts, images, or apply textures to existing models. Four providers with different cost/quality tradeoffs.
Provider Selection
| Provider | Script | Cost | Speed | Best for |
|---|---|---|---|---|
| Meshy (default) | meshy_text_to_3d.py, meshy_image_to_3d.py |
5-20 credits | 2-7 min | Text-to-3D, texturing, low-poly game assets, batch |
| fal.ai Hunyuan3D | fal_hunyuan3d.py |
$0.225 | ~2 min | High-fidelity image-to-3D with PBR, text-to-3D |
| WaveSpeedAI Rapid | wavespeed_rapid.py |
$0.0225 | ~1 min | Bulk iteration, concept validation (16x cheaper) |
| Trellis 2 | trellis2.py |
15-55 credits | 30s-4 min | Precise poly count control, geometry-only fast runs |
| Local Depth | depth_local.py |
Free | ~5s | Offline depth maps, local mesh gen, preprocessing |
Decision guide:
- Quick concept check → WaveSpeedAI ($0.02, fastest)
- Production image-to-3D → fal.ai Hunyuan3D (best PBR quality)
- Text-to-3D → Meshy (only provider with text prompt support + refine pipeline)
- Specific poly budget → Trellis 2 (
--decimation 5000for low-poly) - Batch generation → Meshy (
meshy_batch.pywith manifest) - Free offline depth/mesh → Local Depth (zero API cost, ONNX on-device)
- Depth map as preprocessing → Local Depth + any cloud provider for texturing
Prerequisites
# API key in environment (already in ~/.config/env/secrets.env)
export MESHY_API_KEY="msy_xxx"
Get your API key at: https://www.meshy.ai/settings/api
Quick Start
Test Connection
uv run ~/.claude/skills/meshy/scripts/test_meshy.py --quick
Generate a Model
uv run ~/.claude/skills/meshy/scripts/meshy_text_to_3d.py "a stealth fighter jet, delta wings" \
--model-type lowpoly --format glb --output ./models
Check Balance
uv run ~/.claude/skills/meshy/scripts/meshy_tasks.py balance
Core Workflows
1. Text-to-3D Generation
What ships with it
20 files 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.
- assets/glb-viewer.html 33 KB
- README.md 259 B
- references/api-reference.md 2.8 KB
- references/depth-local.md 3.8 KB
- references/fal-hunyuan3d.md 2.5 KB
- references/trellis2.md 3.1 KB
- references/wavespeed-rapid.md 1.8 KB
- scripts/_meshy_utils.py 16 KB runs code
- scripts/_provider_base.py 4.2 KB runs code
- scripts/depth_local.py 23 KB runs code
- scripts/fal_hunyuan3d.py 8.9 KB runs code
- scripts/meshy_batch.py 8.7 KB runs code
- scripts/meshy_image_to_3d.py 4.2 KB runs code
- scripts/meshy_tasks.py 5.7 KB runs code
- scripts/meshy_text_to_3d.py 3.6 KB runs code
- scripts/meshy_texture.py 3.4 KB runs code
- scripts/networks.py 19 KB runs code
- scripts/test_meshy.py 4.8 KB runs code
- scripts/trellis2.py 6.8 KB runs code
- scripts/wavespeed_rapid.py 4.7 KB runs code
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.
- 10d ago First seen · 257 lines · 126 tokens per session scan B d62df9f16989
meshy is a skill published in the GitHub repository tdimino/claude-code-minoan (41 stars, last pushed 2d ago), licensed MIT. It adds 126 tokens to every session and 2,576 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 1 finding (unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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