List every prompt collection in the free ecommerce ChatGPT prompt library at xpay.sh/prompts — 43 store-type categories (skincare, coffee, apparel, …) and 10 marketing-task sets (email, SEO, product descriptions, ads, …). Returns each collection's slug, label, kind, prompt count, and page URL.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | Filter to store-type categories or marketing tasks. Omit for all. |
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?
No annotations are provided, so the description carries the full burden. It correctly describes a read-only listing operation with no side effects, detailing the returned data. It discloses the library scope (free ecommerce ChatGPT prompts). No contradictions.
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 sentence that efficiently conveys the purpose, scope, and return fields without any redundant information. It is front-loaded with the main action and detail, earning 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?
Given no output schema, the description fully explains the return fields. It covers purpose, optional filter, and output structure. For a simple listing tool with one optional parameter, this is complete and leaves no ambiguity.
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 description adds meaning to the 'kind' parameter by explaining its filter options (store-type categories vs. marketing tasks) and the default (omit for all). Since the schema already has an enum and description, the description provides additional context about the categories and tasks, improving usability.
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 clearly states the tool lists every prompt collection in the free ecommerce ChatGPT prompt library, specifying the 43 store-type categories and 10 marketing-task sets. It also lists the return fields (slug, label, kind, prompt count, page URL), making the purpose unambiguous and distinct from sibling tools like 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the structure of collections (categories vs. tasks) and the optional 'kind' filter. It implies usage for browsing collections before selecting prompts, but does not explicitly contrast with siblings or state when not to use it.
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.
Each tool has a clearly distinct purpose: retrieving prompts by collection, by ID, listing collections, and searching across prompts. No ambiguity between them.
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.
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.
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.