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AppBoard.pro product discovery

appboard_product_details

Get everything AppBoard knows about one product: what it does, its pricing model, platforms, use cases, target audiences, community metrics, any discount code, and its alternatives. Use after appboard_find_products when the user asks about a specific product. Taxonomy terms link to their browse pages; an alternative that has its own AppBoard collection carries alternativesPage — the URL to open for it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesthe product's AppBoard slug, as returned by appboard_find_products

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral transparency burden. It implies a read-only operation ('Get everything AppBoard knows') and does not mention any side effects. However, it does not explicitly state that the tool has no side effects or is read-only, which would be more transparent. The description is otherwise clear about the data returned.

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?

The description is concise yet informative, consisting of two sentences that efficiently convey the tool's scope, usage context, and special link behaviors. It is well-structured without unnecessary repetition or verbosity.

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 the lack of an output schema, the description sufficiently covers the tool's functionality, including the type of data returned and how to interpret certain fields (e.g., alternativesPage URL). It provides enough context for an agent to use the tool correctly without additional assumptions.

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?

The schema already provides a complete description of the 'slug' parameter ('the product's AppBoard slug, as returned by appboard_find_products'), and the tool description does not add further semantic details beyond that. Since schema coverage is 100%, the baseline of 3 is appropriate.

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 the tool's purpose: retrieving comprehensive product details from AppBoard. It explicitly lists the types of information returned (e.g., pricing, platforms, alternatives) and distinguishes itself from siblings by specifying it is for a single product and should be used after appboard_find_products.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Use after appboard_find_products when the user asks about a specific product.' It also explains how to handle returned links (taxonomy terms link to browse pages, alternativesPage is a URL to open), giving clear instructions on when and how to use the tool.

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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