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 skills/andrewbartels1/solidworksmcp-python/feature-tree-reconstructionnpx skills add andrewbartels1/SolidworksMCP-python --skill feature-tree-reconstructiongit 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/skills/andrewbartels1/solidworksmcp-python/feature-tree-reconstruction)<a href="https://agentmods.dev/skills/andrewbartels1/solidworksmcp-python/feature-tree-reconstruction"><img src="https://agentmods.dev/badge/skills/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 | $0.00066 | $0.00564 |
| Opus 5 | $0.00033 | $0.00282 |
| Sonnet 5 | $0.00013 | $0.00113 |
| Haiku 4.5 | $0.00007 | $0.00056 |
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 4d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature-Tree Reconstruction
Use this skill when the original model is available and appearance-first guessing would be risky.
Objective
Produce a safe, evidence-backed reconstruction workflow that starts from model inspection and only executes after the family and first-feature strategy are approved.
Workflow
- Inspect before planning:
open_modelget_model_infolist_features(include_suppressed=True)get_mass_propertiesclassify_feature_tree
- Classify feature family and confidence:
revolve,extrude,sheet_metal,advanced_solid,assembly,drawing,unknown
- Delegate by family:
sheet_metaland unsupported advanced families: VBA-aware reconstruction path- simple part families: direct MCP checkpoint plan
- assembly: component-first decomposition, part-level reconstruction per component
- Retrieve supporting evidence before execution:
- local worked examples
- tool-catalog pages
- recent error/remediation history
- Execute conservatively:
- propose 3-6 checkpoint steps only
- require human approval before each irreversible step
- Verify and store:
- capture resulting feature-family alignment
- compare mass properties and key dimensions
- log failures and remediation for future runs
Output Contract
Always return:
familyconfidence(high/medium/low)evidence(top items used)warnings(contradictions, missing evidence)recommended_workflowcheckpoint_plan(3-6 steps)requires_human_confirmation(true/false)
Guardrails
- Never reconstruct from silhouette only when the source model is available.
- Never produce a monolithic 20-step build plan before family acceptance.
- Do not continue execution when confidence is low and contradictory evidence exists.
- If family is
unknown, force additional inspection and user clarification before build. - For sheet metal and unsupported operations, route to VBA-aware planning instead of guessing direct tool calls.
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.
- 4d ago First seen · 68 lines · 66 tokens per session scan A fee86e87cb4e
feature-tree-reconstruction is a skill published in the GitHub repository andrewbartels1/SolidworksMCP-python (68 stars, last pushed today), licensed MIT. It adds 66 tokens to every session and 564 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…