AIUseCaseHub

Search AI deployments with filters

hybrid_search_usecases

Read-only

Search AI use cases with hybrid full-text and vector ranking. Supports provider, industry, geography, technology, customer, partner, and boolean case-type filters.

Input Schema

TableJSON Schema

Name	Required	Description
`isRag`	No	Filter for retrieval-augmented generation deployments.
`limit`	No	Maximum results requested. Public previews return at most 3; personal-key access permits up to 20.
`query`	Yes	Natural-language query.
`country`	No	Filter by country code, for example US or GB.
`isVoice`	No	Filter for voice AI deployments.
`industry`	No	Filter by the deployment industry.
`isAvatar`	No	Filter for AI avatar deployments.
`isVision`	No	Filter for computer vision deployments.
`isCopilot`	No	Filter for copilot deployments.
`isAgentCase`	No	Filter for AI agent deployments.
`isFineTuning`	No	Filter for model fine-tuning deployments.
`partner_name`	No	Filter by implementation partner.
`customer_name`	No	Filter by the company adopting AI.
`cloud_provider`	No	Microsoft, AWS, GCP, or comma-separated values.
`isMultiAgentCase`	No	Filter for multi-agent deployments.
`isMicrosoftFabric`	No	Filter for Microsoft Fabric deployments.
`technologies_used`	No	Filter by technology name.
`isSustainabilityCase`	No	Filter for sustainability use cases.

Schema Changelog

Changes observed during successful MCP inspections.

Changed16 schema fields changedSep 6, 2026
- addedInput schema / properties / country / description
```
Added value: +"Filter by country code, for example US or GB."
```
- addedInput schema / properties / customer_name / description
```
Added value: +"Filter by the company adopting AI."
```
- addedInput schema / properties / industry / description
```
Added value: +"Filter by the deployment industry."
```
- addedInput schema / properties / isAgentCase / description
```
Added value: +"Filter for AI agent deployments."
```
- addedInput schema / properties / isAvatar / description
```
Added value: +"Filter for AI avatar deployments."
```
- addedInput schema / properties / isCopilot / description
```
Added value: +"Filter for copilot deployments."
```
- addedInput schema / properties / isFineTuning / description
```
Added value: +"Filter for model fine-tuning deployments."
```
- addedInput schema / properties / isMicrosoftFabric / description
```
Added value: +"Filter for Microsoft Fabric deployments."
```
- addedInput schema / properties / isMultiAgentCase / description
```
Added value: +"Filter for multi-agent deployments."
```
- addedInput schema / properties / isRag / description
```
Added value: +"Filter for retrieval-augmented generation deployments."
```
- addedInput schema / properties / isSustainabilityCase / description
```
Added value: +"Filter for sustainability use cases."
```
- addedInput schema / properties / isVision / description
```
Added value: +"Filter for computer vision deployments."
```
- addedInput schema / properties / isVoice / description
```
Added value: +"Filter for voice AI deployments."
```
- addedInput schema / properties / limit / description
```
Added value: +"Maximum results requested. Public previews return at most 3; personal-key access permits up to 20."
```
- addedInput schema / properties / partner_name / description
```
Added value: +"Filter by implementation partner."
```
- addedInput schema / properties / technologies_used / description
```
Added value: +"Filter by technology name."
```
First observedSep 6, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare the tool read-only and non-destructive. The description adds meaningful behavioral context by disclosing the hybrid ranking mechanism, which is not visible in the annotations or schema. It does not cover rate limits or result shape, but the read-only annotation lowers the burden for safety-related details.

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?

Two tight sentences with no fluff: the first fronts the core action and ranking behavior, the second summarizes the available filter dimensions. Every phrase 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 rich schema fully documents all 18 filter parameters, including the limit nuance about public previews. The absence of an output schema is acceptable because 'Search AI use cases' clearly implies a list of matching use cases. The main missing piece — explicit routing against sibling tools — is already accounted for in the usage-guidelines dimension.

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 every parameter. The description only summarizes filter categories at a high level and adds no syntax, format, or default information beyond the schema, keeping it at the baseline of 3.

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 ('Search AI use cases') with a clear resource, and the phrase 'hybrid full-text and vector ranking' distinguishes it from the sibling tools. The title reinforces scope with 'with filters'.

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 guidance is implied by the phrase 'hybrid full-text and vector ranking' — this suggests it is the choice when both retrieval modes are wanted. However, the description never explicitly tells an agent when to choose this tool over search_usecases or vector_search_usecases, nor does it name alternatives.

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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