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concordance

by com.narrowhighway
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original_words

[WORD · internal] The original-language words behind a verse (Hebrew/Greek, with Strong's where known) — FOUND in the lexicon, never generated. Returns the tagged words AND coverage {tagged, total, untagged_positions, untagged_words, complete}: the tagged words are not the whole verse (Greek ~44% tagged, Hebrew ~98%), and the untagged words are shown, never dropped. Pass ref, e.g. 'John 3:16'.

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": {
      "ref": "<ref>"
    },
    "name": "original_words"
  }
}

Input Schema

NameRequiredDescriptionDefault
refYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / ref / maxLength
      Added value: +4000
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden, and it does substantial work: it discloses data provenance (lexicon-sourced, never generated), the fact that tagging is partial (~44% Greek, ~98% Hebrew), and that untagged words are never dropped. It omits any note on permissions, rate limits, or caching, but the behavioral core is well covered.

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?

Front-loaded with the purpose, then return shape, then invocation. Slightly dense and mildly redundant in restating the untagged-words behavior alongside the coverage field list, but every sentence is substantive.

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?

With no output schema and no annotations, the description supplies what an agent needs: it names the returned fields (coverage: tagged, total, untagged_positions, untagged_words, complete), explains what they mean, and warns about partial tagging. Nothing essential to correct invocation is missing.

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 description coverage is 0% and the single parameter has no documentation in the schema, so the description must compensate. It does, by naming the parameter and giving a concrete format example ('John 3:16'), though it doesn't discuss limits like the 4000-char maxLength or accepted reference forms beyond the one example.

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: retrieves the original-language (Hebrew/Greek) words behind a verse, with Strong's tagging. The provenance claim ('FOUND in the lexicon, never generated') further separates it from generative siblings like define or word_study.

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 shows how to call it ('Pass ref, e.g. John 3:16') but never says when to choose it over the many nearby siblings such as word_study, define, lookup, or thesaurus. Usage is implied by the resource name rather than stated.

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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