software_get_robotCommercial profile of one robot (specs, pricing, viability score), plus its software tier and profile status. The commercial fields are identical in all three get_robot variants - the layer flag is the only difference.
| Name | Required | Description | Default |
|---|---|---|---|
| robot_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds useful context about cross-variant consistency (commercial fields identical, layer flag is the only difference) and enumerates the returned profile components, which goes beyond the annotations without contradicting them.
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?
Two concise sentences with no filler. The first sentence front-loads the core purpose and return fields, and the second adds a valuable cross-variant clarification.
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 one-parameter, read-only tool with no output schema, the description adequately covers purpose, key return fields, and the relationship to sibling variants. It lacks explicit return structure or status value details, but it is sufficient for selection and basic invocation.
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?
The schema has only robot_id with no description, and schema description coverage is 0%. The description does not explain the format, origin, or expected values of robot_id, so it fails to compensate for the lack of parameter documentation.
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 clearly states the tool returns a commercial profile for one robot (specs, pricing, viability score) plus software tier and profile status. It also distinguishes itself from the hardware and mechanical get_robot variants by noting the commercial fields are identical and only the layer differs.
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?
The description implies this variant is for software-layer coverage and clarifies that the three get_robot variants share commercial fields. However, it does not explicitly state when to prefer this over software_get_robot_software or list tools, so exclusions are not fully articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The layer prefixes and action verbs make most tools clearly distinct, but the three list_robots variants return the same catalogue and the three get_robot variants share identical commercial fields, creating real selection ambiguity. The descriptive warnings like 'call one, not three' help but do not fully resolve the overlap.
All 27 tools follow a uniform <layer>_<action>_<object> snake_case pattern with consistent verbs: get, list, compare. There are no mixed naming conventions or stylistic deviations.
27 tools is above the comfortable range and is inflated by triplication: list_robots, get_robot, compare_robots, list_signals, and system_status are repeated across layers with only minor differences. A layer parameter could consolidate a large portion of the surface without losing functionality.
As a read-only intelligence platform, the set covers catalogue listing, comparison, robot profiles, BOM details, block analysis, dependency analysis, signals, and system health across hardware, mechanical, and software layers. The main gap is the lack of a consolidated multi-layer robot view, though agents can compose one from the three get_robot variants.