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Agent Ready by WorkPods (hosted)

Request a full WorkPods audit

request_full_audit

Files a request for a full WorkPods audit of a site: how AI answers (ChatGPT, Gemini, Perplexity, Google AI Overviews) mention the brand and its competitors, search rankings and a prioritised fix list, done by WorkPods with paid data. Use it only when the person asks for it and gives their own work email. There is no charge. A WorkPods operator reviews the request and emails the report to that address within 3 working days. result has requested, domain and next (what to tell the person). The email goes to WorkPods and is not stored by this service.

Input Schema

NameRequiredDescriptionDefault
emailYesThe person's own work email address.
websiteYesThe site to audit, as a domain or URL, such as example.com.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, it discloses that WorkPods staff manually review the request, email the report within 3 working days, and that there is no charge. It also states the result fields and clarifies that the email goes to WorkPods and is not stored by this service.

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 front-loaded with the purpose, then usage condition, then operational details and result shape. Every sentence carries useful information, with no repeated or filler wording.

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?

Although there is no output schema, the description explains the result fields, the turnaround time, the no-charge policy, the privacy handling, and the user prerequisite. That is complete enough for an agent to decide and invoke the tool correctly.

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%, and the schema already describes both parameters as the person's own work email and the site to audit. The description reinforces the "own work email" condition but adds no syntax, format, or validation detail beyond the schema.

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 uses a specific verb and resource: "Files a request for a full WorkPods audit of a site." It then details what that audit covers, including AI answer mentions, competitors, search rankings, and a prioritised fix list, which clearly distinguishes it from sibling check/crawl/draft 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?

It gives explicit when-to-use and when-not-to-use guidance: only when the person asks for it and provides their own work email. It does not name a specific sibling alternative, so it falls short of the top score, but the practical trigger 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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