leaderboard
Global analyst reputation leaderboard. Free.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Global analyst reputation leaderboard. Free.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
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 provided, so the description must solely disclose behavioral traits. It does not mention that the tool is read-only, safe, or what side effects (if any) occur. 'Free' is ambiguous and insufficient for an agent to determine all behavioral implications.
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?
Extremely concise, but at the expense of clarity. 'Free' adds minimal value and could be omitted or integrated. Structure is front-loaded but lacks substantive sentences.
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 the simple input and no output schema, the description should still convey basic expectations like whether the tool is read-only, what the return format is, and example usage. It fails to do so, leaving the agent under-informed.
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 only parameter 'limit' is not explained in the description. With 0% schema description coverage, the agent gets no help understanding how 'limit' affects the result (e.g., maximum number of entries).
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 indicates it is a 'global analyst reputation leaderboard,' implying a read operation to retrieve rankings. However, it lacks an explicit verb like 'get' or 'list,' and does not differentiate from sibling tools that may also involve reputation data.
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?
No guidance on when to use this tool versus alternatives. The word 'Free' hints at no cost but does not clarify usage context or prerequisites.
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: listing tickers, estimates, submissions, consensus, AI thesis, leaderboard, and verdict. No two tools overlap in function; even 'ai_thesis' and 'read_estimate' are differentiated by the synthesis aspect.
Naming is mixed: some tools use verb_noun (list_estimates, submit_estimate) while others are bare nouns (leaderboard, verdict). This inconsistency could confuse an agent expecting a uniform pattern, though the names are individually clear.
With 8 tools, the server covers the core workflows of an earnings oracle (browsing, analyzing, submitting, evaluating) without excessive or insufficient tools. The count is well-scoped for the domain.
The tool surface appears complete: discovery (list_tickers), data retrieval (list_estimates, ticker_consensus, read_estimate, ai_thesis), contribution (submit_estimate), and post-earnings analysis (verdict) plus reputation (leaderboard). No obvious gaps.