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CaeliaEve

AutoCAD MCP Ultra

by CaeliaEve

Find Entities in Region

analysis_find_in_region
Read-only

Find every entity inside a rectangular area in AutoCAD drawings. Use crossing selection to locate all hits, with optional field projection or compact output to manage large result sets.

Instructions

Find all entities within a rectangular region (crossing selection).

Uncapped: a window over a busy drawing returns every hit. Project with fields and/or compact before widening the window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
x1YesRegion minimum X
x2YesRegion maximum X
y1YesRegion minimum Y
y2YesRegion maximum Y
fieldsNoProject to these fields, in this order (e.g. ['handle','type','layer']); 'properties.<key>' reaches one nested value. Omit for the full record; an unknown name errors and lists the valid ones.
compactNoReturn a columnar {fields, rows, count, offset, total, truncated, next_offset} envelope instead of dicts: much cheaper per row, and the only shape that reports truncation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already mark readOnlyHint=true, but the description adds important behavioral context beyond that: it warns that queries are uncapped and can return every hit in a busy drawing, with a performance-oriented mitigation. This helps the agent anticipate large results and plan output 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 compact, front-loaded with the core purpose, and every sentence adds value. The uncapped warning and the fields/compact advice are directly actionable without any filler.

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

Completeness5/5

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

Given the output schema exists, annotations cover the read-only nature, and the input schema fully documents parameters, the description is complete. It even covers the most important operational caveat—uncapped result size—which is exactly the kind of context an agent needs before invoking the tool.

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 100%, and the schema already explains all six parameters, including field projection syntax, unknown-name behavior, and the compact envelope. The description reinforces a useful strategy for fields/compact but does not add new parameter-level meaning beyond what the schema provides.

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 states a specific action ('Find all entities'), a specific resource ('within a rectangular region'), and even clarifies the selection mode ('crossing selection'). This clearly distinguishes it from broader listing tools like entity_list and selection-based siblings without needing to inspect schemas.

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?

The description gives clear practical guidance: results are uncapped, so users should project with fields and/or compact before widening the window. It does not explicitly name sibling alternatives, but the context around when and how to invoke it safely is clear and actionable.

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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