search_usecasesSearch curated AI use cases using the default hybrid ranking. Use this when an agent has a natural-language search term.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum results requested. Public previews return at most 3; personal-key access permits up to 20. | |
| query | No | Alias for search_term. | |
| search_term | Yes | Natural-language search term. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / limit / descriptionAdded value: +"Maximum results requested. Public previews return at most 3; personal-key access permits up to 20."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by noting the 'default hybrid ranking' and that the corpus is 'curated', but it does not disclose details like result format or access-tier limits, which are only present in the parameter schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. It front-loads the core action and ranking behavior, then gives a crisp usage condition. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only search tool with a fully described schema, the description covers the essential selection criteria and behavioral expectations. It does not explain what the response contains, but no output schema exists and the main missing piece is explicit sibling differentiation, which is partially hinted at by 'default hybrid ranking'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are already well documented in the schema. The description adds a small amount of guidance by framing the tool around 'natural-language search term', which aligns with the search_term parameter, but it does not meaningfully extend the parameter semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Search curated AI use cases') and identifies the ranking method ('default hybrid ranking'), which clearly distinguishes this tool from the sibling tools hybrid_search_usecases and vector_search_usecases. The verb and resource are specific and the scope is immediately understandable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this tool when an agent has a natural-language search term, giving a clear condition for selection. However, it does not mention when not to use it or explicitly point to alternatives such as hybrid_search_usecases or vector_search_usecases, so it stops short of full exclusion guidance.
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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Three of the four tools are search variants with overlapping behavior: search_usecases and hybrid_search_usecases both use hybrid ranking, and vector_search_usecases partially overlaps with the default semantic behavior. The descriptions provide some clues (filters vs. natural-language), but the boundary between the search tools remains unclear.
The search tools follow a clean pattern of [modifier_]search_usecases, and get_usecase_details uses a standard verb_noun form. The only minor deviation is singular 'usecase' in get_usecase_details versus plural 'usecases' in the search tools.
Four tools is a reasonable size for a focused use-case hub. Having three search variants is slightly redundant, but the count is still well within an appropriate scope.
The set covers the core retrieval workflow: search across multiple modes and fetch full details by ID. Minor gaps include the absence of a browse/list-all tool or explicit pagination, but agents can likely accomplish the intended tasks.