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orthotomeo

by io.github.jrainsberger

Search concordance (lemma)

concord_lemma
Read-only

Complete-or-fail concordance: every words row in corpus whose lemma, dStrong, or (with by="surface") exact inflected surface form matches query. Route lemma/Strong's-number/surface-word lookups here, never by writing SQL or guessing occurrences from memory. This deployment caps one concordance result at 2000 occurrences and refuses anything broader, reporting the exact match count in the error. Call count first when a query might be broad - count is never capped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
byNooptional match column override: lemma, dstrong, or surface. Omit for auto-detect (dStrong shape, else lemma) - surface must always be requested explicitly, it is never guessed
queryYesa lemma (e.g. ἄφεσις), a disambiguated Strong's number (e.g. G0859, H7225G), or (with by="surface") the exact inflected word as it appears in the verse
corpusYesword-tagged corpus to search: TAGNT (Greek NT), TAHOT (Hebrew OT), Swete (LXX surface), OSS-LXX-lemma (LXX lemma)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
engineYes
sourcesNo
citationsYes

TDQS

A4.9/5.0
Behavior5/5

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

Discloses behavioral traits beyond annotations: caps at 2000 occurrences, refuses broader queries, reports exact match count in error. readOnlyHint already indicates non-destructive, but description adds critical constraints.

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 sentences, each meaningful. Front-loaded with 'Complete-or-fail concordance'. No superfluous text every sentence earns its place.

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 complexity (parameter options, multiple corpora, limits) and existence of output schema, the description is fully complete: covers purpose, usage, parameters, behavior, and provides guidance on alternatives.

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%, baseline is 3. Description adds value by explaining the 'by' parameter (auto-detect vs explicitly request surface), and clarifies query format (lemma, Strong's number, surface). Slightly above baseline.

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?

Clearly states the tool searches concordance by lemma, dStrong, or surface form. Distinguishes from sibling tools like 'count' and 'concord_phrase' by directing lemma/Strong's-number/surface-word lookups here.

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 advises to route lookups here instead of writing SQL or guessing from memory, and recommends calling 'count' first when a query might be broad. Provides clear when-to-use and when-not-to-use guidance.

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