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theosib

FreeCAD MCP Server

by theosib

tracked_recompute

Recompute FreeCAD documents and track changes in object validity to understand the impact of modifications on your design.

Instructions

Recompute a document and track what changed.

Snapshots every object's validity before recomputing, then diffs against the post-recompute state. Reports:

  • new_errors: objects that were valid before but are now invalid

  • resolved: objects that were invalid but are now valid

  • persistent_errors: objects that remain invalid

  • valid_count: number of objects that stayed valid

Use this instead of raw recompute to understand the impact of changes.

Args: doc_name: Document name. Empty string uses the active document.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_nameNo
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it snapshots object validity before recomputing, diffs post-recompute states, and reports specific categories of changes (new_errors, resolved, persistent_errors, valid_count). This covers the core operational logic and output structure, though it doesn't mention potential side effects like performance impact or error handling.

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

Conciseness5/5

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

The description is well-structured and front-loaded, starting with the core purpose. Each sentence adds value: the first explains the action and tracking, the next details the snapshot and diff process, then lists the report categories, and finally provides usage guidance and parameter clarification. There is no wasted text, and it efficiently conveys necessary information.

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?

Given the complexity of a recompute operation with tracking, no annotations, and no output schema, the description does a good job of explaining what the tool does, how it behaves, and what it reports. It covers the input parameter semantics and usage context adequately. However, it lacks details on potential limitations, error conditions, or performance implications, which could be relevant for a mutation tool.

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

Parameters4/5

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

The description adds meaningful semantics beyond the input schema. The schema has 0% description coverage and only defines 'doc_name' as a string with a default. The description explains that 'doc_name' is the 'Document name' and specifies that 'Empty string uses the active document,' clarifying the default behavior and usage context, which compensates for the low schema coverage.

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

Purpose5/5

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

The description clearly states the specific action ('recompute a document and track what changed') and distinguishes it from alternatives by mentioning 'use this instead of raw recompute to understand the impact of changes.' It explicitly contrasts with a sibling tool (implied 'raw recompute') and explains the unique tracking functionality.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool versus alternatives: 'Use this instead of raw recompute to understand the impact of changes.' This directly addresses the decision point between this tool and other recompute methods, offering clear context for selection.

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

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