text_spellcheck
utilpeek: Spellcheck a text with suggestions. For counts and readability use text_stats. Returns the words not in the language's word-frequency dictionary (pyspellchecker), with positions (offset, line, column) and up to max_suggestions suggestions by edit distance; numbers, acronyms, CamelCase, ...
This record as markdown: /tools/dev-tanod-tanod/text-spellcheck.md
What text_spellcheck does on Tanod
AI agents use text_spellcheck to create or update resources in Tanod, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Tanod environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
text | string | Yes | The text (at most 200,000 characters). |
language | string | — | Dictionary: en (default), es, fr, de or pt. |
max_suggestions | integer | — | Corrections suggested per misspelled word (0-10, default 5). |
Parameters from the server's own tool schema.
Why text_spellcheck is rated Medium
An AI agent can call text_spellcheck faster than any human can review: one bad instruction and it creates or modifies resources in Tanod by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs text_spellcheck safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Tanod, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For text_spellcheck, this is the rule to start with:
text_spellcheck stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Tanod, apply this rule, and every text_spellcheck call is checked against it from then on.
Questions about text_spellcheck
utilpeek: Spellcheck a text with suggestions. For counts and readability use text_stats. Returns the words not in the language's word-frequency dictionary (pyspellchecker), with positions (offset, line, column) and up to max_suggestions suggestions by edit distance; numbers, acronyms, CamelCase, URLs and emails are skipped. A dictionary lookup, not grammar or context aware. Typically under 1 s (up to 2 s on a language's first use). Price: USD 0.002. Free: 10 utilpeek calls per IP per UTC day. The submitted text is never logged or stored. Docs: https://tanod.dev/learn/spell-check-api.html. It is categorised as a Write tool in the Tanod MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
text_spellcheck accepts 3 parameters: text, language, max_suggestions. Required: text. The full parameter table on this page comes from the server's own tool schema.
Register the Tanod MCP server in PolicyLayer and add a rule for text_spellcheck: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Tanod. Nothing to install.
text_spellcheck is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the text_spellcheck rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for text_spellcheck. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
text_spellcheck is provided by the Tanod MCP server (https://tanod.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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