hardware_list_robotsList the robot catalogue with filters, including semiconductor tier and payload. Returns the same catalogue as the mechanical and software variants - call one, not three. Pick this one to filter by semiconductor tier.
| Name | Required | Description | Default |
|---|---|---|---|
| pays | No | ||
| tier | No | ||
| limit | No | ||
| offset | No | ||
| categorie | No | ||
| min_score | No | ||
| min_payload | No | ||
| in_scope_only | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive. The description adds useful behavioral context that all three list variants return the same catalogue, preventing redundant calls, which goes beyond the annotations.
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 sentences efficiently state the purpose and usage guidance without excess. Front-loaded with the core action and immediately differentiates from siblings.
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?
Given 8 optional filter parameters and no output schema, the description fails to explain most parameters, their defaults, or the response format, leaving significant gaps for an agent to correctly invoke the tool with proper filters.
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 0% description coverage for its 8 parameters. The description mentions only 'semiconductor tier and payload,' which maps to two parameters (tier, min_payload), but leaves the other six unexplained, insufficiently compensating for the lack of schema descriptions.
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 lists the robot catalogue with filters, mentioning semiconductor tier and payload. It explicitly distinguishes this tool from the mechanical and software variants by noting the catalogue is the same and this one is for semiconductor tier filtering.
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?
Provides explicit guidance: 'call one, not three' and 'Pick this one to filter by semiconductor tier,' telling the agent exactly when to use this tool versus the sibling list variants.
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.