Borrowing it
Nothing to install: this file belongs to andrewbartels1/SolidworksMCP-python. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/andrewbartels1/SolidworksMCP-python/main/.github/prompts/feature-tree-reconstruction.prompt.mdgit clone --depth 1 https://github.com/andrewbartels1/SolidworksMCP-pythonWrote 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/andrewbartels1/solidworksmcp-python/feature-tree-reconstruction)<a href="https://agentmods.dev/commands/andrewbartels1/solidworksmcp-python/feature-tree-reconstruction"><img src="https://agentmods.dev/badge/commands/andrewbartels1/solidworksmcp-python/feature-tree-reconstruction.svg" alt="Measured on agentmods" 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 | $0.00422 |
| Opus 5 | $0.00017 | $0.00211 |
| Sonnet 5 | $0.00007 | $0.00084 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
feature-tree-reconstruction 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
Run an inspect-classify-delegate pass before planning any reconstruction.
Inputs:
- Target model path: ${input:modelPath:C:/Users/Public/Documents/SOLIDWORKS/SOLIDWORKS 2026/samples/learn/Baseball Bat.SLDPRT}
- User goal: ${input:userGoal:Reconstruct the model faithfully and identify the right MCP vs VBA workflow}
- Extra context: ${input:extraContext:Optional screenshot notes, constraints, or dimensions}
Required workflow:
- If a model path is provided, open the original file first.
- Read the active state with:
get_model_info()list_features(include_suppressed=True)get_mass_properties()classify_feature_tree()
- Summarize the part family, confidence, evidence, and any warnings.
- Trace the likely parent-child dependency chain from the feature tree.
- Decide whether the path is:
- direct MCP solid modeling
- VBA-backed advanced part modeling
- assembly planning
- drawing workflow
- insufficient evidence, inspect more
- Only then propose the next reconstruction steps.
Output requirements:
- Start with
Classification Summary - Then
Why This Classification - Then
Recommended Workflow - Then
Next Concrete Steps - If confidence is low, say what additional evidence is needed before building
Rules:
- Do not infer “simple extrude” from silhouette alone if the original file is available.
- If the tree shows sheet metal markers (
Sheet-Metal,Base-Flange,Edge-Flange,Sketched Bend,Unfold,Fold), preserve that family in the recommendation. - If only sketch/profile features are visible, treat the result as provisional and combine it with mass properties and images before committing to a rebuild path.
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 · 39 lines · 35 tokens per session scan A f88ec20eb774
feature-tree-reconstruction is a command published in the GitHub repository andrewbartels1/SolidworksMCP-python (70 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 422 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 2026-09-06.
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