get_leaderboardReturn the public WebAnalyzer leaderboard: the highest-scoring analyzed websites with their name, URL and 0-100 score, best first.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many entries to return (1-100). Default 20. |
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?
Annotations already declare the operation is read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond annotations by specifying that results are public, sorted best-first, and include score fields, which covers the main return semantics an agent needs.
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, focused sentence that immediately states the resource and key output characteristics. Every element earns its place with no filler or redundant phrasing.
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 simple read-only leaderboard tool with one optional parameter and no nested objects, the description plus annotations and schema are fully sufficient. It communicates what the tool returns, the ordering, and the field composition, so an agent can invoke it correctly without missing information.
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 schema has 100% description coverage for the single optional 'limit' parameter, including constraints and default value. The tool description does not add further parameter detail, but none is needed since the schema already fully documents it; baseline 3 is appropriate.
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 returns the public WebAnalyzer leaderboard, with specific details on what is included (website name, URL, 0-100 score) and ordering (best first). This distinguishes it from sibling tools that analyze or retrieve individual website analyses.
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 implies use when the agent needs a high-level public ranking of analyzed websites rather than an individual site's analysis. It doesn't explicitly name alternatives or exclusions, but the 'public leaderboard' framing gives clear context for when it is appropriate.
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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Each tool has a clearly distinct purpose: analyze_website starts a new analysis, get_analysis retrieves a past result, and get_leaderboard lists top-scoring sites. There is no meaningful overlap or ambiguity between them.
All tool names follow the same verb_noun pattern: analyze_website, get_analysis, get_leaderboard. The verbs and nouns are clear, consistent, and predictable.
Three tools is well-scoped for a focused analysis service: one to trigger analysis, one to fetch results, and one to access the leaderboard. Each tool earns its place without redundancy.
The surface covers the full workflow for the domain: run a website analysis, retrieve that analysis by ID, and view the public leaderboard. No update or delete operations are necessary for this one-shot, immutable analysis model.