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orthotomeo

by io.github.jrainsberger

Interlinear reading view

interlinear
Read-only

Returns a row-aligned reading view for every word in a verse (or one word, if word is given): original text, transliteration, gloss (via lexicon_lookup), grammar, and manuscript attestation stacked per word - the composed display shape for a study reading view, built on parse and lexicon_lookup rather than any new query. This is the most complete per-word view; use parse or attestation when you want only one of those facets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bookYesUSFM book code (e.g. GEN, PSA, MAT, REV) or the full English book name, any case (e.g. Genesis, matthew)
wordNo1-based word_no within the verse; omit for every word in the verse
verseYesverse number
corpusYesword-tagged corpus: TAGNT, TAHOT, Swete, OSS-LXX-lemma
chapterYeschapter number

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
wordsYes
engineYes
sourcesNo

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds context: it is a 'composed display shape' built on 'parse and lexicon_lookup rather than any new query', which informs agents about no side effects and composite nature.

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?

Two sentences: first describes output comprehensively, second gives usage guidance. No unnecessary words, front-loaded with key information.

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?

Given the tool's complexity (5 params, output schema exists), the description covers purpose, facets, composite nature, and usage alternatives. No gaps remain.

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 baseline is 3. Description adds that omitting 'word' returns every word in the verse, which clarifies the parameter's effect beyond the schema's '1-based word_no' description.

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?

The description clearly states the tool returns a 'row-aligned reading view' for each word, listing specific facets. It distinguishes from siblings by noting this is the 'most complete per-word view' and directing to 'parse' or 'attestation' for single facets.

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?

Explicitly says when to use this tool ('most complete per-word view') and when not to ('use parse or attestation when you want only one of those facets'). Also mentions it is built on other tools, not a new query.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct operation or output type. Even closely related tools like concord_lemma, concord_phrase, and count have clear differences in what they return (full concordance vs. phrase match vs. tally), and tools like interlinear, parse, and lexicon_lookup are well-differentiated by their descriptions.

Naming Consistency3/5

Tool names follow multiple patterns: some are single-word verbs (cite, count, parse), others are compound nouns (attestation, interlinear), and some use underscores in verb_noun or noun_noun form (concord_lemma, get_passage, lexicon_lookup). While each name is descriptive, the lack of a uniform convention reduces consistency.

Tool Count5/5

12 tools effectively cover the domain of biblical text analysis: retrieval, concordance, parsing, lexical lookup, attestation, and citation. This count is neither too sparse nor overwhelming, and each tool serves a clear purpose within the workflow.

Completeness4/5

The tool surface covers core operations for biblical study (verse retrieval, morphological analysis, lexicon lookup, concordance, citation). Minor gaps exist, such as the lack of tools for searching by English word or for handling Hebrew texts beyond limited lexicon lookup, but these do not severely hinder typical workflows.

Resources