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language_search

Find D&D 5e languages by name and get matching entries. Use when you know the content type; otherwise, use omnisearch.

Instructions

Search D&D 5e languages by name. Returns a list of matching entries. Use when you know the content type; if unsure of the type, use omnisearch instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return
queryYesName or partial name to search for
fieldsNoFields to include in each result (default: all fields). E.g. ["name","cr","source"]
rulesetNoWhich ruleset to search. Omit to use the configured default ("2024"); pass "2014" to override.2024
include_homebrewNoWhen true, also search TheGiddyLimit/homebrew content alongside official results

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It discloses the basic read behavior (search by name) and the return shape (a list of matching entries), but adds no deeper behavioral context such as matching semantics, source scoping, ordering, or limits. Adequate but not rich.

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 earning its place: purpose, return value, and usage routing. Purpose is front-loaded and there is no repetition of schema content or filler.

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?

For a straightforward search tool this is nearly complete: the schema documents every parameter fully, and the description covers purpose, matching basis, return type, and tool selection. With no output schema, the return description is minimal but adequate; slightly more detail on result shape would push it higher.

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 all five parameters (query, limit, fields, ruleset, include_homebrew) are already documented with descriptions, defaults, and an enum. The description adds only the name-based matching hint that maps to query, so the baseline 3 applies.

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

Purpose5/5

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

States a specific verb and resource: Search D&D 5e languages by name. The language-specific scope is unambiguous among the many sibling *_search tools, and the closing sentence explicitly differentiates it from omnisearch, so an agent can distinguish this tool without opening the schema.

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

Usage Guidelines5/5

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

Gives explicit when-to-use guidance (when you know the content type) and names the alternative with its trigger condition (if unsure of the type, use omnisearch instead). This provides clear tool-selection routing comparable to the high-quality calibration example.

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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