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Find the Old English word(s) matching an ASCII spelling

anglo_deromanize
Read-onlyIdempotent

Find the real Old English word(s) whose ASCII spelling matches this input — the inverse of anglo_romanize. romanize is deeply lossy (th←þ or ð, dropped macrons), so this is a LOOKUP against words already cached: attested spellings come back as source=dictionary. If none match, a single best-effort reconstruction (source=reconstruction, approximate=true) — a guess, not attested. Coverage grows as words are cached.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesASCII-spelled Old English text to resolve back to real orthography. Returns the attested dictionary spelling(s) whose romanization matches (source=dictionary, exact) — several may match one ambiguous key. On a miss, a single best-effort reconstruction (source=reconstruction, approximate=true), a guess: Old English romanization is deeply lossy (th←þ or ð, dropped macrons/dots), so the dictionary hit is the reliable answer.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
candidatesYes
approximateYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/non-destructive, and the description adds substantive behavior beyond them: it is a LOOKUP against cached words, hits return source=dictionary, misses return a single reconstruction flagged approximate=true, and coverage grows as words are cached. This is exactly the kind of outcome-shaping detail an agent needs.

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 core purpose, then the lossy-romanization rationale and fallback behavior. Dense but efficient; the parenthetical asides are justified, though the em-dash nesting is slightly heavy.

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?

An output schema exists so return values needn't be explained, yet the description still conveys the source/approximate distinction that governs interpretation. For a single-parameter lookup tool, nothing material is missing.

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 100% and the parameter's own description already explains the lossy romanization and source values. The tool description adds only the 'several may match one ambiguous key' nuance, so it largely repeats the schema — baseline 3 is appropriate.

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 (find the real Old English word(s) whose ASCII spelling matches) and explicitly names its inverse, anglo_romanize, so the agent can distinguish it from that sibling without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clearly establishes the direction of use relative to anglo_romanize and explains the dictionary-vs-reconstruction outcome, giving strong context. It stops short of explicit when-not guidance or naming other alternatives, but the inverse framing is unambiguous.

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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