get_prompt
Get one prompt by its id, with the full template body, variables, recommended model, pro tip, and source URL.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Prompt id from search_prompts or get_collection_prompts. |
ecommerce-prompts-mcp
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A4.1/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description clearly indicates this is a read operation returning specific data. It does not mention error handling or permissions, but the nature of a GET is transparent enough.
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?
One sentence, efficiently packed with key information (verb, resource, result fields), no waste.
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 no output schema, the description sufficiently lists return fields. It also references sibling tools for obtaining the id, making retrieval context clear.
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 coverage is 100% with a clear parameter description. The tool description does not add extra semantics beyond what the schema already provides, so baseline 3 applies.
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 clearly states 'Get one prompt by its id' and enumerates the returned fields (full template body, variables, recommended model, pro tip, source URL), distinguishing it from sibling tools like search_prompts or get_collection_prompts.
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?
No explicit when-to-use guidance is provided, but the parameter description implies that the id should be obtained from search_prompts or get_collection_prompts, giving indirect context. However, no direct comparison or exclusion criteria are stated.
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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TDQS
A4.2/5.0
Disambiguation5/5
Each tool has a clearly distinct purpose: retrieving prompts by collection, by ID, listing collections, and searching across prompts. No ambiguity between them.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case (get_collection_prompts, get_prompt, list_collections, search_prompts), making them predictable and easy to understand.
Tool Count5/5
With 4 tools, the server is well-scoped for browsing and retrieving prompts from a library. Each tool serves a necessary function without redundancy or excess.
Completeness5/5
The tool surface covers all essential read operations: listing collections, retrieving individual prompts, getting all prompts in a collection, and searching. For a read-only prompt library, no obvious gaps exist.