get_usecase_detailsFetch detailed information for a single AI use case by RowKey/id.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No | Alias for row_key. | |
| row_key | Yes | The RowKey/id returned by search tools. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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 clear. The description adds the 'single AI use case' scope but does not disclose output format, retention, or other behavior; this is acceptable given the read-only annotation.
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 a single, well-structured sentence that states the action, the target, and the lookup mechanism without any wasted words. It is front-loaded and easy to parse.
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-by-key tool, the description plus annotations and schema provide enough context for an agent to select and invoke it. The lack of an output schema makes 'detailed information' slightly vague, but not critically incomplete.
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?
The input schema covers both parameters fully (100%), including the alias relationship between id and row_key. The description adds minimal semantic value beyond restating the lookup key, so the baseline 3 is appropriate.
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 uses a specific verb ('Fetch'), a clear resource ('detailed information for a single AI use case'), and the lookup key ('by RowKey/id'). This clearly distinguishes the tool from the sibling search tools, which return lists of cases.
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 phrase 'by RowKey/id returned by search tools' indicates this tool is meant to be used after finding a specific case via search. It gives clear context for when to use it, though it does not explicitly list alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.