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Wizeb AI-Native Index

Email the PDF scorecard

email_index_report

Builds the full PDF scorecard (score, tier, six-dimension breakdown, every answer next to the AI-native end state, and the three fastest improvements) and emails it to the user, with a copy to the Wizeb team so a human can follow up. Ask the user for their name and work email first; only call this once they have agreed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesThe user's name
emailYesThe user's work email address
answersYesThe same 30 answers passed to score_index.
companyNoCompany name (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, idempotentHint=false), the description discloses important side effects: the email is sent to the user, a copy goes to the Wizeb team, and a human will follow up. It also notes the consent requirement, adding meaningful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the primary action and recipients. The second sentence adds essential prerequisite guidance without padding. Every part earns its place.

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?

The description covers the action, recipients, and consent precondition. It does not describe the return value or failure behavior, but since there is no output schema and this is primarily a side-effect tool, the missing return details are a minor gap.

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%, so the schema already documents all parameters. The description reinforces that name and work email must be collected from the user and that answers are the same 30 passed to score_index, but it adds little semantic detail beyond what the schema provides.

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 states a specific action: builds a full PDF scorecard and emails it to the user, with a copy to the Wizeb team. This clearly distinguishes it from siblings like get_enhanced_index_report, which are retrieval tools rather than send/email tools.

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?

The description gives explicit preconditions: ask for the user's name and work email first, and only call after the user has agreed. It does not explicitly name alternatives or when-not-to-use cases, but the context and prerequisites are clear enough for correct invocation.

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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