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get_tool

Full detail for a specific AI tool by slug. Returns description, links, pricing, similar tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesTool slug (e.g. unity-mcp, meshy)

Schema Changelog

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

  1. Changed4 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedInput schema / properties / context
      Removed value: -{
      -  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
      -  "type": "string"
      -}
    • changedInput schema / properties / slug / description
      Previous value: -"URL slug of the tool (e.g. unity-mcp, meshy)"New value: +"Tool slug (e.g. unity-mcp, meshy)"
    • changedInput schema / required
      Previous value: -[
      -  "slug",
      -  "context"
      -]New value: +[
      +  "slug"
      +]
  2. Changed3 schema fields changed
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / context
      Added value: +{
      +  "description": "Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\"",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "slug"
      -]New value: +[
      +  "slug",
      +  "context"
      +]
  3. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses return components, but does not mention behavior on missing slug, error handling, or side effects. For a simple read tool, the description is adequate but not rich.

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?

A single, front-loaded sentence that conveys the tool's purpose and return values with no superfluous words. Ideal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple one-parameter schema and no output schema, the description sufficiently covers what the tool returns and how it is invoked. Minor omissions like not-found behavior are not critical for this low-complexity tool.

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 for the single slug parameter is 100%, with a clear description and examples. The tool description adds only 'by slug' which is already implicit in the schema, providing no meaningful extra semantics.

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 retrieves full details for a specific AI tool by slug, listing return contents (description, links, pricing, similar tools). This distinguishes it from siblings like compare_tools or explore, making its purpose unambiguous.

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?

The description implies use for single-tool lookups via slug, but does not explicitly contrast with siblings or state when not to use it. Since siblings like compare_tools or get_trending suggest different use cases, some guidance is inherent but not explicit.

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

A4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: comparing, exploring, getting details, trending, listing, and resolving. No overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., compare_tools, get_tool, list_collections). Even 'explore' is a single verb, fitting the pattern.

Tool Count5/5

7 tools is well-scoped for a tool discovery server, covering browsing, details, comparison, and recommendations without being overwhelming.

Completeness4/5

Covers most discovery needs (browse, trend, compare, detail) but lacks a general search tool or filtering by features, a minor gap.