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Word Orb — English vocabulary for reader glossaries

search_words

Read-onlyIdempotent

Search stored English headwords or definition text by prefix or fuzzy matching. Returns matching entries, which may be empty. Requires a Word Orb key; counts toward account quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query (min 2 chars)
fieldNoSearch fieldword
fuzzyNoEnable fuzzy matching
limitNoMax results (1-50)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior beyond annotations: results may be empty, a Word Orb key is required, and the call counts toward account quota. This is valuable operational context with no contradiction.

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

Conciseness5/5

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

Three short sentences, each carrying distinct information: search scope/modes, return behavior, and access/quota constraints. There is no filler, and the most important behavioral info is front-loaded.

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

Completeness4/5

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

The description plus the fully documented schema gives the agent enough to call the tool correctly: query constraints, field enum, fuzzy option, limit range, and quota impact. It does not describe the shape of matching entries, and there is no output schema, but for a simple filtered search this is a minor gap.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds semantic meaning beyond the schema by tying 'headwords or definition text' to the field parameter and 'prefix or fuzzy matching' to how q and fuzzy behave. This helps the agent understand parameter interactions rather than just their raw types.

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 identifies the verb ('Search'), the resource ('stored English headwords or definition text'), and the matching modes ('prefix or fuzzy'). It does not explicitly differentiate from siblings like lookup_words or search_by_meaning, but the scope is specific enough to be understood on its own.

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?

The description implies when the tool is useful: for partial-prefix or fuzzy searches rather than exact lookups. However, it never explicitly routes the agent away from alternative siblings or states when not to use this tool, so usage guidance is only implicit.

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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