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.
git clone --depth 1 https://github.com/brs077/CNC-design-control-MCPWrote 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/commands/brs077/cnc-design-control-mcp/package-for-sale)<a href="https://agentmods.dev/commands/brs077/cnc-design-control-mcp/package-for-sale"><img src="https://agentmods.dev/badge/commands/brs077/cnc-design-control-mcp/package-for-sale/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/commands/brs077/cnc-design-control-mcp/package-for-sale"><img src="https://agentmods.dev/badge/commands/brs077/cnc-design-control-mcp/package-for-sale.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 | $0.00017 | $0.00148 |
| Opus 5 | $0.00009 | $0.00074 |
| Sonnet 5 | $0.00003 | $0.00030 |
| Haiku 4.5 | $0.00002 | $0.00015 |
Grade A, and why
package-for-sale 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 11d 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
Package Design for Marketplace
Help me package my CNC design for selling online.
- Ask which marketplace: Etsy, Cults3D, or Gumroad
- Ask about the design: name, description, material, dimensions
- Check for existing design files (G-code, SVG, DXF) or offer to generate them
- Use
package_designto bundle all files - Use
generate_listing_descriptionto create optimized listing copy - If format conversion is needed, use
convert_design_format
Present the final package contents and listing description for review.
$ARGUMENTS
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.
- 11d ago First seen · 19 lines · 17 tokens per session scan A 9e94f1ea7c1f
package-for-sale is a command published in the GitHub repository brs077/CNC-design-control-MCP (1 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 148 once invoked, about $0.0001 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 commands, from other repositories
product-image
Generates professional product photos (3 or 5 shots) from a photo folder or a store URL, in minimalist, elegant or UGC style, with product-fidelity verification.
pickle-clips
Batch reference→video clips for a store's gen5 SKUs (Veo free + Kling paid), spend-gated.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.