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Turns what a caller typed into the catalog word it names

ud_resolve_word
Read-onlyIdempotent

Turns what a caller typed into the catalog word it names, or up to five candidates. Pass q (such as harbors).

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": {
      "q": "<q>"
    },
    "name": "ud_resolve_word"
  }
}

Input Schema

NameRequiredDescriptionDefault
qYesWhat the caller typed, 1 to 255 characters.
fieldsNoComma-separated top-level keys to keep: match, candidates.

Output Schema

NameRequiredDescriptionDefault
dataNo
metaNoThe day of the answer, and the page cursor of a list.
linksNoLinks of the answer.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds one genuine behavioral fact beyond that: the call may return a single match or a set of up to five candidates. It does not say how candidates are ranked, what happens at zero matches, or how ties are broken.

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?

Two short sentences, front-loaded with the purpose, with no filler. The trailing 'Pass `q` (such as harbors)' is mildly redundant with the required-parameter schema but does clarify input shape quickly.

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

Completeness3/5

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

Because an output schema exists, the description need not explain return values, and the mention of 'up to five candidates' covers the key surprise. However, for an ambiguity-resolving tool, the definition never explains what a 'catalog word' is or how confident matching is decided, leaving a meaningful gap an agent would care about.

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?

Schema description coverage is 100%, so both `q` and `fields` are already documented in the schema, and an output schema exists. The description adds only an illustrative value ('such as harbors') for `q` and says nothing about `fields` projection, so the baseline of 3 is appropriate.

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 states a specific transformation (typed input -> the catalog word it names) plus a bounded fallback ('or up to five candidates'), which is a clear verb+resource statement. It does not name or contrast with any sibling such as ud_get_name or ud_list_word_categories, so sibling differentiation is left to the agent.

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

Usage Guidelines2/5

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

There is no guidance on when to reach for this resolver versus a direct lookup tool like ud_get_name, nor any precondition or exclusion. The only hint is the phrase 'up to five candidates', which implies fuzzy/ambiguous input, but that is inference rather than stated usage.

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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