View top referrers ranked by total commission earned. Shows agent ID, referred volume, and commission for each entry. FREE — rate-limited only. [pricing: {"cost":"0","currency":"FREE","type":"free","network":"eip155:8453"}]
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max entries (default: 20, max: 100) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does a good job. It explicitly states 'FREE — rate-limited only,' and indicates a read-only behavior by saying 'View' and 'Shows.' It also lists the fields returned. This is useful context beyond what the schema alone provides, though it could go further by mentioning any authentication requirements or data freshness.
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 compact and front-loaded: two sentences plus a pricing JSON block. Every sentence adds value (purpose, output fields, and cost/rate-limit). No wasted words.
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 one optional parameter and no output schema. The description sufficiently explains the return contents (agent ID, referred volume, commission) and the ranking criterion. It could be a 5 if it explicitly noted descending sort order or pagination behavior, but the 'top' implies sorting and the limit parameter handles pagination.
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?
Schema description coverage is 100% for the single 'limit' parameter, which already documents default and max values. The description adds no additional parameter semantics, so it appropriately hits the baseline of 3.
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's function: 'View top referrers ranked by total commission earned.' It specifies the resource (top referrers) and the ranking metric. However, it does not explicitly differentiate from sibling tools like flipr_referral_stats or flipr_agent_stats, so it earns a 4 rather than a 5.
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 usage for viewing a leaderboard but provides no explicit guidance on when to use this tool versus alternatives. There is no mention of 'Use this for X, use other for Y,' so usage context is only inferred from the name and description.
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 targets a distinct aspect of the Flipr ecosystem: game info, health/status, flipping action, pot/opportunity monitoring, agent stats, referral program, and withdrawal. No two tools have overlapping purposes; even similar-sounding ones like flipr_opportunity and flipr_pot are clearly differentiated by ROI analysis.
All tool names follow a consistent 'flipr_<noun>' snake_case pattern (e.g., flipr_agent_stats, flipr_flip). The naming is predictable and intuitive, making it easy for an agent to understand the hierarchy of operations.
With 18 tools, the server covers the full scope of a betting game with referral features. Each tool serves a clear role without bloat. The count feels well-scoped for the domain, neither too sparse nor overwhelming.
The tool surface covers core gameplay (flip, health, game info), opportunity analysis (pot, opportunity, history, subscription), agent/referral management, and payout. A minor gap is the lack of a tool to retrieve an agent's own flip history beyond aggregated stats, but this does not hinder primary use cases.