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Rankwise

List content opportunities

list_opportunities
Read-onlyIdempotent

List the workspace's ranked content opportunities: topics where AI engines answer questions the brand is not cited for, scored by demand, citation gap and feasibility. Dismissed topics are left out. Each item says whether a brief or article already covers it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYes
opportunitiesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: dismissed topics are filtered out, results are ranked/scored on three named dimensions, and each row carries a covered/not-covered flag. It stops short of describing ordering or pagination.

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?

Three compact sentences with no filler, front-loaded with the core identity of the resource before the scoring/exclusion details. Slightly dense in the middle sentence, but every clause 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?

An output schema exists, so return values needn't be spelled out, and annotations handle safety. What's present (definition, ranking basis, exclusion rule, coverage flag) is enough to call the tool, though the limit parameter and result ordering remain unaddressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the single 'limit' parameter, so the description carries the burden of explaining it — and it says nothing about limit, defaulting, or the 1-100 range. With low coverage the description should compensate, and here it does not.

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?

It names a specific verb and resource ('list... content opportunities') and goes further by defining what an opportunity actually is: 'topics where AI engines answer questions the brand is not cited for.' The scoring dimensions (demand, citation gap, feasibility) and the coverage note make it trivially distinguishable from siblings like dismiss_opportunity or refresh_opportunities.

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

Usage Guidelines3/5

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

Usage is only implied by the verb 'list'. It never says when to reach for this versus refresh_opportunities (to regenerate results) or how it relates to dismiss_opportunity beyond noting dismissed topics are excluded. Adequate context, but no explicit when/when-not routing.

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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