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English spell check with suggestions

spell_check
Read-only

English spell check with suggestions. Check spelling. Fast English spell checker (US and UK): flags misspellings with ranked suggestions, offsets and an auto-corrected text. Drop-in replacement for the retired Bing Spell Check API (format=bing).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoproof (default: spelling + repeated words) or spell (spelling only) (e.g. proof)
textYesText to check (max 20,000 characters) (e.g. I recieve alot of emails abuot the the project.)
wordsNoComma-separated custom words to accept (brand names, jargon) (e.g. TidyData,Kubernetes)
formatNoLeave empty for the full response, or bing for the Bing Spell Check v7 response shape
languageNoen-US (default), en-GB or en (any English). Also accepts mkt=en-US like Bing (e.g. en-US)
max_suggestionsNo1-10 suggestions per error (default 4) (e.g. 4)
ignore_uppercaseNoSkip ALL-CAPS words like acronyms (true/false, default true) (e.g. true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, openWorld). The description adds genuine value beyond them: it discloses the return shape (ranked suggestions, offsets, auto-corrected text) and the format=bing compatibility mode, which matters since there is no output schema.

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 and kept to a few sentences. There is mild redundancy between the title, 'Check spelling', and the opening phrase, but nothing is bloated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only text-processing tool with a fully documented schema but no output schema, the description supplies the missing return-value context (suggestions, offsets, corrected text) and language/format scope. A brief note on limits or error behavior would make it fully complete.

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 coverage is 100%, so all seven parameters are already documented with examples in the schema. The description only echoes the format=bing behavior and adds no syntax or default details beyond what the schema already provides, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('English spell check', 'flags misspellings') and conveys scope (US/UK English, ranked suggestions). It is clearly distinguishable from siblings like dictionary_define or detect_language, though it never names those alternatives explicitly.

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?

Usage is implied by the purpose (check spelling of text) and the Bing-compatibility note hints at a migration use case, but there is no explicit when-to-use versus dictionary_define/detect_language guidance and no stated prerequisites or exclusions.

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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