latin
Server Details
Grounds LLMs in real Latin: Wiktionary lemmas, Morpheus inflections, citations.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.6/5 across 3 of 3 tools scored.
search_latin and get_inflections both provide declension/conjugation tables, which could cause slight confusion. However, descriptions clarify that search_latin is the primary lookup with senses, while get_inflections is a fallback for unexpanded matches. lemmatize_latin is distinct for morphological analysis.
All tool names follow a consistent verb_noun pattern with lowercase and underscores: get_inflections, lemmatize_latin, search_latin. No mixing of styles.
Three tools is a small but focused set for Latin language lookup, covering search, inflection tables, and morphological analysis. Slightly minimal, but each tool serves a distinct purpose within the domain.
The tool set covers the main tasks for Latin text analysis: looking up a word with senses and tables, retrieving full inflection tables separately, and analyzing inflected forms. Missing might be dictionary definitions beyond Wiktionary, but core functionality is well-covered.
Available Tools
3 toolsget_inflectionsGet a Latin inflection tableARead-onlyIdempotentInspect
Fetch the full declension (nominals) or conjugation (verbs) table for a lemma identified by a search result's inflection handle (vards_id + word_class). Use this only when a search ran without inline forms or left a match un-expanded — a default search already returns each match's table inline. Returns Markdown plus the table as structuredContent with the shape {"result": } per the declared outputSchema — switch on result.category ('nominal' | 'verbal' | 'not_found') before reading the body. Content from en.wiktionary.org (CC BY-SA 4.0).
| Name | Required | Description | Default |
|---|---|---|---|
| vards_id | Yes | The Wiktionary page title (the lemma) from a search result's inflection handle, e.g. 'amo', 'aqua'. | |
| word_class | Yes | The part-of-speech section from a search result's inflection handle, e.g. 'verb', 'noun', 'adjective'. |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive. Description adds data provenance (from en.wiktionary.org, CC BY-SA 4.0), explains output structure (Markdown + structuredContent with result.category), and details the handle parameters. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the main purpose. It contains several sentences but each provides necessary information (when to use, output shape, data source). Slightly long but no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (inflection tables for nominals/verbs), the description covers input, output shape, category field handling, usage conditions, and data source. Output schema exists, so return values are fully specified; description complements it well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions. The description adds context by explaining the parameters come from a 'search result's inflection handle' and providing examples (e.g., 'amo', 'aqua'), adding value beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches declension/conjugation tables for Latin lemmas using a search result's inflection handle. It distinguishes from siblings by specifying the input source and the condition when to use (when search ran without inline forms).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'use this only when a search ran without inline forms or left a match un-expanded', providing clear when-to-use guidance and contrasting with default search behavior. Also explains how to process the output (switch on result.category).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lemmatize_latinMorphologically analyze a Latin formARead-onlyIdempotentInspect
Analyze one inflected Latin form with the Morpheus morphological analyzer: its lemma(s) plus the grammatical reading (person, number, tense, mood, voice, case…). Useful when you want the morphology itself — for the dictionary entry, search_latin already resolves inflected queries on its own. Returns Markdown plus the analysis as structuredContent matching the declared outputSchema. Results are cached server-side. Analyses via the Perseids Morpheus service.
| Name | Required | Description | Default |
|---|---|---|---|
| word | Yes | One inflected Latin word form to analyze, e.g. 'amavit', 'aquam'. Macrons optional. |
Output Schema
| Name | Required | Description |
|---|---|---|
| word | Yes | |
| found | Yes | |
| source | No | |
| analyses | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and idempotentHint. The description adds that results are cached and uses the Perseids Morpheus service, providing useful context beyond annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and front-loaded, efficiently communicating purpose, usage guidance, and behavioral context in three sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (one parameter, output schema exists, rich annotations), the description is complete: it explains what it does, when to use it, how it works (caching, service), and output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage for the single parameter 'word'. The main description does not add additional semantic detail beyond schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes one inflected Latin form with the Morpheus morphological analyzer, returning lemma(s) and grammatical reading. It distinguishes itself from the sibling tool search_latin, which is used for dictionary entry resolution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Useful when you want the morphology itself' and contrasts with search_latin. Also mentions caching and the underlying service, helping the agent decide when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_latinLook a Latin word upARead-onlyIdempotentInspect
Look a Latin word up on Wiktionary and return its senses plus full declension/conjugation tables — attested content, not invented. Any form of the word works; an inflected query is resolved to its lemma automatically (via previously cached paradigms or the Morpheus analyzer) and the result notes the resolution. Returns Markdown plus the same result as structuredContent matching the declared outputSchema.
Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | A SINGLE Latin word, not a phrase — one per call. Any form works: an inflected form ('amavit') is resolved to its lemma ('amo') automatically via cached paradigms or the Morpheus analyzer, and the result says so. Macrons are optional ('amo' and 'amō' both work). For English→Latin, you must already know the Latin word — this dictionary is keyed by Latin headwords. | |
| max_forms | No | Optional override for how many inflection tables to expand this call (0–12). On an uncached query each table is one politely paced upstream fetch, so high values on cold queries are slow. Omit for the server default. | |
| include_forms | No | When true (default), each match's full declension/conjugation table is returned INLINE — usable cases/tenses in ONE call, no follow-up get_inflections. Set false for a cheap screen of which entries exist. Bounded by a per-search cap — use max_forms to adjust per call. |
Output Schema
| Name | Required | Description |
|---|---|---|
| found | Yes | False when nothing matched. |
| query | Yes | |
| source | No | |
| entries | No | |
| handles | No | |
| language | Yes | |
| resolved_from | No | The original inflected query when resolved; else empty. |
| search_method | No | How the match was found: 'direct' = the query itself matched; 'lemma_index' = an inflected form resolved via a previously cached paradigm; 'morpheus' = resolved via the Morpheus morphological analyzer. |
| resolved_lemma | No | The lemma actually searched when resolved; else empty. |
| forms_truncated | No | How many handles did NOT get an inline table because the per-search cap was reached. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, idempotentHint, etc. Description adds caching behavior, rate limit error handling, content licensing (CC BY-SA 4.0), auto-lemmatization resolution, and return format (Markdown + structuredContent). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured, front-loaded with main action. Every sentence adds useful information, though slightly lengthy. Still concise for the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (auto-lemmatization, caching, rate limiting, output schema), the description covers all necessary aspects. Output schema exists so return values are explained elsewhere. Complete for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions. Description adds value beyond schema by explaining caching implications for max_forms (high values slow on cold queries). Slight improvement over baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool looks up a Latin word on Wiktionary and returns senses plus full declension/conjugation tables. It distinguishes from siblings by emphasizing it handles any inflected form and returns both senses and tables, while sibling names suggest more specific operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on input constraints: any form works, auto-lemmatization, macrons optional, and English→Latin requires knowing the Latin word. Mentions caching and rate limiting. Could be more explicit about when to use this vs siblings, but overall helpful.
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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