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 agentmods add agents/andrewbartels1/solidworksmcp-python/agents-and-testinggit clone --depth 1 https://github.com/andrewbartels1/SolidworksMCP-pythonWhat 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 | $0.00000 | $0.03721 |
| Opus 5 | $0.00000 | $0.01861 |
| Sonnet 5 | $0.00000 | $0.00744 |
| Haiku 4.5 | $0.00000 | $0.00372 |
Grade A, and why
agents-and-testing 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agents and Prompt Testing
This guide is written for people who know SolidWorks well but are new to LLM agents and AI-assisted workflows.
What Are Agents? (Plain-Language Overview)
If you know SolidWorks, think of agents like this:
| SolidWorks concept | Agent equivalent |
|---|---|
| Design Intent | Your prompt — what you're trying to build |
| Custom toolbars / macros | Agents — specialists trained for specific tasks |
| Feature Manager checklist | Schema — structured output that validates the result |
| Macro recorder | Skill — a reusable SOP the agent follows |
| Feature history | SQLite log — every prompt and result saved locally |
You write a prompt describing what you want (material, printer, geometry constraints). The agent responds with structured, validated output — not just a chat reply — that can feed directly into your SolidWorks MCP workflow.
What Agents Are Available
Three specialist agents live in .github/agents/:
solidworks-print-architect
Use when: Designing parts for 3D printing — tolerances, snap fits, overhangs, print orientation, build volume checks.
Example output includes:
- Material tradeoffs (PLA vs PETG vs ABS)
- Snap-fit clearance ranges with risk level
- Which face to put on the print bed and why
- Build volume check against your specific printer
solidworks-mcp-skill-docs
Use when: Building SolidWorks MCP workflows, creating tutorials, planning tool sequences from sketch to feature.
Example output includes:
- Step-by-step MCP tool call sequence
- Decision table for tool selection
- Troubleshooting fallbacks
- Demo walkthrough using sample parts from your SolidWorks install
solidworks-research-validator
Use when: Fact-checking material specs, looking up printer build volumes, comparing sourcing options before committing to geometry changes.
Example output includes:
- Short answer first
- Evidence table with source and confidence
- Recommended decision with risk level
- Open questions to resolve before CAD work
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.
- 2d ago First seen · 458 lines · 0 tokens per session scan A b8ea0b6b9134
agents-and-testing is an agent published in the GitHub repository andrewbartels1/SolidworksMCP-python (65 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,721 tokens. 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.