Get the agent leaderboard showing top-performing agents ranked by total conversions. Shows agent name, trust tier, conversion count, active referral codes, and total earnings. Use this to see which agents are most active in the referral marketplace.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of entries to return (default 10, max 50) | |
| offset | No | Offset for pagination (default 0) |
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 readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds behavioral context by specifying ranking order ('ranked by total conversions') and listing the exact fields returned, which goes beyond the annotations.
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 three sentences, front-loaded with the core action, and every sentence adds value. No wasted words or redundancy.
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?
The tool is simple with no output schema, but the description adequately explains what the leaderboard contains and how it is ranked. The schema covers pagination parameters, so no critical information is missing.
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 input schema already fully describes both parameters (limit and offset) with defaults and constraints (100% schema coverage). The description adds no additional parameter details, so the baseline score of 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 'Get the agent leaderboard' with a specific resource and action. It details what data is shown (agent name, trust tier, conversion count, etc.) and distinguishes it from sibling tools like check_balance or search_deals, which serve different purposes.
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 provides a clear use case: 'Use this to see which agents are most active in the referral marketplace.' It doesn't explicitly mention alternatives or exclusions, but no sibling tool offers leaderboard functionality, so the context is sufficient.
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.
The discovery-oriented tools—search_deals, compare_vendors, track_changes, and plan_stack—overlap in purpose and can be confused, especially for queries like 'What's cheaper than Vercel?' or 'Are free tiers being removed?'. The referral and account tools are clearly distinct, but the overlapping query surface lowers the overall disambiguation quality.
Most tools follow a consistent verb_noun pattern such as check_balance, submit_referral_code, and request_payout. Two tools deviate: 'leaderboard' is a bare noun and 'my_referral_codes' uses a possessive prefix, creating minor inconsistency.
Twelve tools is well within the ideal range and each tool covers a meaningful part of the AgentDeals domain: deal discovery, referral management, agent registration, payouts, and social routing. None of the tools feel redundant or extraneous.
The tool surface covers the main agent lifecycle well: registration, referral code submission and retrieval, balance checking, payouts, and friend management. Minor gaps exist—there is no way to update or remove a submitted referral code, and the payout address must be configured via an out-of-band API endpoint.
