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One rival up close

rival_detail
Read-onlyIdempotent

One rival from the person's own checks: its age and registrar, DR, what it does, and every question and AI where it was named and the person's site was not, with that AI's words about it. Use it for "how old is that site and what's its DR?" about a rival, or "what did the AIs say about Linktree?". Rivals are seen only through the person's own questions; for any other site use domain_age and domain_rating.

Input Schema

NameRequiredDescriptionDefault
siteNoOne of your sites, if the rival is in one site's list.
rivalYesThe rival's name or domain, e.g. "Linktree" or "heya.page".

Output Schema

NameRequiredDescriptionDefault
viewYesWhat this answer is; "none" for a question back, a plain no, or nothing there yet (see message).
rivalNo{ name, domain, whatTheyDo, ageDays, registeredAt, registrar, dr, namedCount, perEngine, questionsWon, namedOverYou: [{ question, aiLabel, quotes }] }.
messageNoWhen view is "none": what to tell the person.
drCreditNoDomain Rating by Ahrefs (ahrefs.com).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The description adds meaningful context beyond annotations: rivals are seen only through the person's own questions, and the result includes every question and AI where the rival was named and the person's site was not. This clarifies data provenance and scope limitations. It does not need to explain return format because an output schema exists, but auth/rate-limit context is absent.

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?

The description is front-loaded and every clause contributes useful scope or alternative guidance. It is slightly dense and could be split for readability, but it does not waste sentences.

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?

Given the output schema and read-only annotations, the description supplies the important missing context: the tool only works on rivals observed in the person's own questions, lists all relevant questions and AI mentions, and points elsewhere for general domain age/rating.

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 both parameters are already documented in the input schema. The description does not add syntax or meaning beyond the schema's own explanation of when to supply site versus rival. Baseline 3 is appropriate.

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 resource and enumerates exactly what is returned: age, registrar, DR, what the rival does, and every question/AI mention with AI commentary. It also explicitly distinguishes this tool from domain_age and domain_rating for sites outside the person's own checks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives concrete use cases in quotes (age/DR about a rival, what AIs said about Linktree) and explicitly names the alternative tools for any site not in the person's own questions. The when-to-use and when-not-to-use boundaries are clear.

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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