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get_word_study
Read-onlyIdempotent

Greek or Hebrew word-page data from the same indexes as /bible/greek and /bible/hebrew. Pass a slug or a Strong’s number. [no key]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNo
strongsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
slugNo
glossNo
lemmaNo
strongNo
languageNo
transliterationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "gloss": {
      +      "type": "string"
      +    },
      +    "language": {
      +      "type": "string"
      +    },
      +    "lemma": {
      +      "type": "string"
      +    },
      +    "slug": {
      +      "type": "string"
      +    },
      +    "strong": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "transliteration": {
      +      "type": "string"
      +    },
      +    "url": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "url"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world, so the safety profile is covered. The description adds useful context beyond that: the data source indexes and the '[no key]' auth note, which tells the agent no API key is required. It does not describe failure behavior for a bad slug/Strong's value, so this is moderate added value rather than rich disclosure.

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 compact fragments, front-loaded with the resource and its provenance, then the input convention, then the auth note. Every element earns its place and there is no padding or repetition.

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?

The tool is low complexity (two optional params) and an output schema exists, so return values need not be explained. Annotations cover safety. The remaining gaps are the slug-vs-Strong's semantics and the lack of routing versus search_word_study, which leaves the definition just barely sufficient for correct selection and invocation.

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 0%, so the description must carry parameter meaning, and it does identify the two inputs by name and nature (slug, Strong's number). It falls short on format details (e.g., Strong's numbering like G26/H1234), length limits, and whether slug and Strong's may be passed together or are mutually exclusive, leaving real ambiguity at 0% schema coverage.

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 names a specific resource (Greek or Hebrew word-page data) and its provenance (the same indexes as /bible/greek and /bible/hebrew), and tells the agent what inputs identify a page. It is clear what the tool returns, but it never distinguishes itself from the sibling search_word_study, so an agent must infer that this is the direct-lookup variant.

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?

'Pass a slug or a Strong’s number' implies the invocation pattern, so usage is inferable. However, there is no explicit when-to-use guidance and no mention of when to prefer this over search_word_study, so routing between the two word-study tools is left entirely to inference.

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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