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Add vocabulary for speech recognition

add_vocab
Idempotent

Teach the call's speech recognition words it keeps mishearing (product names, people, jargon). Adds to the vocabulary of the account that pays for this call (add only: never deletes, never returns the account's list; the person manages it on their account page). terms: words to recognize; fixes: {wrong, right} = a known mishearing and the correct word (right is added to the terms too). Max 20 entries per call of this tool, 100 per call, 50 characters each. Corrections apply right away, the word list from the next sentence or the next call. 409: guest call without an account. Returns added {terms, fixes}, total, call_left, reloaded.

Input Schema

NameRequiredDescriptionDefault
fixesNoKnown mishearings: [{"wrong": "Erzähli", "right": "Trello"}].
termsNoWords or short phrases to recognize, e.g. ["Trello"].
sessionYesThe `session` value returned by join.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, idempotentHint=true, destructiveHint=false), the description discloses behavior richly: additive-only semantics, account scoping to the paying account, hard limits (20 entries per invocation, 100 per call, 50 chars), immediate-effect timing, and the 409 guest-call failure mode. It even enumerates the return payload.

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, followed by constraints, timing, error behavior, and return shape — each sentence carries information. It is dense and slightly run-on, and restating return fields is mildly redundant given the output schema, but there is little true filler.

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?

For a mutation tool with an output schema, the description covers everything an agent needs: limits, timing of effect, account scope, failure mode (409 for guest calls), and the return structure. Nothing material is missing for correct invocation.

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%, so the baseline is 3, but the description adds real semantics: `fixes` is a {wrong, right} mishearing/correction pair and, importantly, `right` is also appended to terms. That side-effect is not derivable from the schema and would change how an agent constructs input.

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?

The description opens with a concrete verb+resource: 'Teach the call's speech recognition words it keeps mishearing', immediately clarified with examples (product names, people, jargon). No sibling tool overlaps this function, so an agent can select it unambiguously.

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?

Usage context is clear (correct recurring mishearing errors during a call) and scope is spelled out: add-only, never deletes, and the list is not returned here but managed on the account page. No explicit alternative tool is named, but none exists among the siblings, so the omission is minor.

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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