Whirrwork

Get a robot model

get_robot_model

Read-onlyIdempotent

One commercial robot model: every maker-published spec with its source URL and the date we checked it (unknown specs are absent, never guessed), maker claims labelled as such, list price if published, independent evidence (trials, tests, certifications, documented deployments) with findings, the jobs its type does, and the Whirrwork assessment with its components. Quote specs with their source.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_robot_model"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes	Model id from find_robots_for_job or /api/v1/robot-models

Output Schema

Name	Required	Description
`id`	Yes
`url`	No
`jobs`	No
`name`	Yes
`note`	No
`maker`	No
`specs`	Yes
`types`	No
`status`	No
`summary`	No
`evidence`	Yes
`spec_url`	No
`type_ids`	No
`assessment`	Yes
`list_price`	No	Maker-published list price with source (not a quote)
`specs_note`	No
`provider_id`	No
`maker_claims`	No
`official_url`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 27, 2026

TDQS

A4/5.0

Behavior5/5

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

Beyond the read-only, idempotent annotations, the description discloses important data-quality behavior: unknown specs are absent rather than guessed, maker claims are labelled, sources and check dates are included, and specs should be quoted with their source. This is meaningful context for trusting and citing the returned data.

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

Conciseness4/5

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

The description is front-loaded with the core purpose and then compactly enumerates the returned content. It is a single dense sentence, but nearly every clause adds useful scope or provenance 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?

An output schema exists, so the description need not explain return structure. It still provides rich context about data provenance, missing-value handling, maker-claim labelling, and evidence categories, which is complete for a single-record retrieval 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?

The schema has 100% description coverage and documents the single id parameter, including examples and where to obtain it. The description does not add further parameter semantics beyond what the schema already provides, so the baseline of 3 applies.

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

Purpose4/5

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

The description clearly states this returns one commercial robot model and enumerates the contents: specs, sources, pricing, evidence, jobs, and assessment. It distinguishes the resource from plural search/compare tools by emphasizing 'One', but it does not explicitly name when to prefer compare_robot_models or find_robots_for_job.

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?

Usage is implied: retrieve a single model by id, with the id sourced from find_robots_for_job or the API path. However, there is no explicit guidance on when to use this versus compare_robot_models or when not to use it.

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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