Select Table By Attribute

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=true. The description adds that it modifies the table selection set and performs a cross-verification of counts, which is useful behavioral context, but it does not describe selection behavior edge cases or output format.

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

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

The single sentence is front-loaded and free of filler, directly stating the tool's action. It is efficient, though the extreme brevity leaves little room for structured guidance.

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

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

For a tool with 5 parameters and 0% schema coverage, the description is incomplete: it does not explain required arguments, selection_type semantics, or project/map/table prerequisites. An output schema exists, so return values need not be described, but the input side remains underspecified.

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

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

Schema description coverage is 0% across 5 parameters, so the description must carry the full parameter burden. It hints at a SQL/where-clause parameter, but does not explain aprx_path, map_name, table_name, selection_type, or defaults.

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

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

The description states a specific action (modifying a standalone table selection set by SQL) and an additional behavior (cross-verifying ArcPy-derived counts against the actual selection set). The term 'standalone table' distinguishes it from layer selection siblings, though no alternative tool is explicitly named.

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

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

No guidance is given on when to use this tool versus siblings such as arcgis_pro_select_layer_by_attribute or arcgis_pro_gp_table_select, nor are prerequisites or exclusions stated. The usage context must be inferred from the name alone.

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