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CaeliaEve

AutoCAD MCP Ultra

by CaeliaEve

Select Entities By Layer

analysis_select_by_layer
Read-only

Select all entities on a given AutoCAD layer and return their handles; use compact mode to get exact counts and detect truncation limits.

Instructions

Get all entities on a specific layer. Returns entity list with handles.

Capped at MAX_LIST_LIMIT (default 5000). The plain list cannot say it was capped — the warning goes to the log stream, which most clients never show the model — so use compact=True when the count matters: its total is the layer's real population and truncated states whether the cap fired.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
layer_nameYesLayer name to select entities from

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the readOnlyHint=true annotation, the description discloses a critical hidden behavior: the MAX_LIST_LIMIT cap at 5000 and the fact that the plain list cannot report truncation because the warning only goes to the log stream. It also explains that compact=True exposes the layer's real population via total and indicates truncation via truncated. This is exactly the behavioral context an agent needs.

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 two short paragraphs with no filler. The first sentence states the operation and output; the second paragraph front-loads the cap and gives actionable guidance. Every sentence contributes necessary information.

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?

For a read-only selection tool with an output schema and fully described parameters, the description covers purpose, return type, truncation edge case, and the corrective parameter for accurate counts. Nothing critical is missing for an agent to invoke it correctly.

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?

With 100% schema description coverage, the baseline is already strong, and the compact parameter's schema description is detailed. The tool description adds further value by explaining why compact matters—it is the only shape that reports truncation—and clarifying that total represents the layer's true population. This goes beyond the schema without being redundant.

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 opens with 'Get all entities on a specific layer', a specific verb and resource, and clarifies the return type with 'Returns entity list with handles'. The layer scope distinguishes it from sibling tools that select by type or region, such as analysis_select_by_type and analysis_find_in_region.

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

Usage Guidelines3/5

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

The description gives strong internal guidance about when to use compact=True versus the plain list, explaining the cap and the unreliable log-stream warning. However, it does not explicitly state when to prefer this tool over alternatives like entity_list, selection_filter, or analysis_select_by_type, leaving tool-selection guidance mostly implicit.

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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