Full text of one buying guide by slug: the short answer, key takeaways, every section with its bullets, and the FAQ. Use this to answer 'how do I choose / what size / what should I look for' questions rather than only recommending a product.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Guide slug, e.g. what-size-portable-power-station |
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?
With no annotations, the description carries the behavioral disclosure burden. It clearly discloses the operation's behavior: fetching the full text of a guide, including specific components. It does not cover failure modes or authentication, but for a simple single-slug retrieval tool the disclosed content is substantial.
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 sentences with no filler. The return content is front-loaded, and the usage context follows immediately. Every clause 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 one-parameter retrieval tool with no output schema, the description adequately explains what the tool returns and when to use it. Since there is no output schema, the detailed enumeration of return content is especially valuable and covers what an agent needs.
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 coverage is 100%, and the schema already documents the slug parameter with an example. The description adds only the phrase 'by slug', which does not enhance the parameter's meaning beyond the schema. The baseline of 3 applies because the schema fully handles the single parameter.
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?
Description states a specific verb and resource: 'Full text of one buying guide by slug', and enumerates exactly what is included (short answer, key takeaways, sections, FAQ). It also differentiates itself from the recommend_product sibling by framing the tool as the answer source for how-to-choose questions.
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 second sentence gives explicit guidance on when to use this tool: for 'how do I choose / what size / what should I look for' questions, and contrasts it with recommending a product. It does not name alternative siblings like list_buying_guides or get_product_details, but the usage context is clear enough.
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: searching, comparing, detailing, recommending, listing guides, and retrieving full guide text. There is minimal overlap, and where tools touch the same resource (e.g., search_products vs recommend_product), their descriptions emphasize different entry points.
All six tools follow a consistent verb_noun snake_case pattern: compare_products, get_guide, get_product_details, list_buying_guides, recommend_product, search_products. The naming style is uniform and predictable, making it easy to infer tool behavior from the name alone.
Six tools is well-scoped for a product recommendation and buying guide server. Each tool covers a distinct part of the user journey without unnecessary duplication, and the count feels neither thin nor bloated.
The tool surface covers the full workflow: discovering products via search, understanding categories via guides, comparing options, getting detailed editorial reviews, and receiving a recommendation. No critical dead ends are apparent—users can start from a broad guide or search and reach detailed product information.
