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KD5RYN

b123d-print-mcp

by KD5RYN

build_part

Run a sandboxed build123d part script to validate geometry and report per-variant bounding boxes, volume, solid count, validity, errors, and build timing; cache built pieces for reuse.

Instructions

Run the part script (sandboxed, with a timeout) and report, per variant and part: bounding box size and min/max (mm), volume (mm^3), solid count, is_valid, the Dims values, and any error with its traceback; and under "timing" each piece's face count and build time, with a hint for a piece that is slow or dense. variant: key from VARIANTS ('standard' = ''). parts: comma-separated piece names from build(): build only those (lazy pieces: the others are never built). Built pieces are cached in out/.cache/, so render_preview, section, check and export reuse them while the script, its Dims and the settings stay the same; fresh=True builds again and replaces the cached pieces. Writes no other files. Ends with "before_printing": the review steps this version still needs, each with its call.

Input Schema

NameRequiredDescriptionDefault
nameYes
freshNo
partsNo
variantNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.12

TDQS

A4.1/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does so well: it discloses sandboxing, timeout behavior, cache location and reuse conditions, fresh rebuild semantics, that no other files are written, per-piece timing hints, and error reporting with tracebacks. This is unusually rich behavioral context for a build tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense and front-loaded with the core action and reporting behavior. It is somewhat run-on and packs many details into long clauses, but nearly every clause provides useful operational context rather than filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex build tool with an output schema, the description covers execution environment, cache behavior, output summary, timing hints, errors, and follow-up review steps. The main gap is that it never explains the required `name` argument, which is important context for invoking the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains `variant` (key from VARIANTS, 'standard' = ''), `parts` (comma-separated piece names from build(), lazy pieces skipped), and `fresh` (rebuild and replace cache), but the required `name` parameter is never described.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: run the part script and report per-variant/part geometry, validity, errors, and timing. It also distinguishes itself from render_preview, section, check, and export by explaining cache reuse, though it does not clearly identify the required `name` argument's role in that purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: `parts` limits which pieces are built, lazy pieces are skipped, cached pieces are reused later, and `fresh=True` rebuilds and replaces cache. It also mentions `before_printing` review steps, but does not explicitly compare when to call this versus siblings like `new_part`, `read_part`, or `diagnose_failure`.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.