Check referral program stats for any agent: total volume referred, commission earned, pending payout amount, and number of referred agents. FREE — rate-limited only. [pricing: {"cost":"0","currency":"FREE","type":"free","network":"eip155:8453"}]
| Name | Required | Description | Default |
|---|---|---|---|
| agentId | Yes | The agent ID to look up |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses pricing ('FREE') and rate-limiting ('rate-limited only'), which is useful. It also lists return values, but does not mention auth requirements, error behavior, or the read-only nature. There are gaps, but the provided context is adequate for a simple lookup tool.
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 concise sentence that front-loads the purpose and immediately lists the stats, followed by a compact pricing/rate-limit note. There is zero wasted wording.
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?
This is a simple one-parameter lookup tool with no output schema. The description enumerates exactly what is returned (four stats) and gives the scope ('any agent'). It is fully adequate for an agent to select and invoke the tool correctly.
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%: the only parameter 'agentId' is documented as 'The agent ID to look up'. The description does not add further meaning about the parameter's format or source, so it adds no value beyond the schema. Baseline 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's function: 'Check referral program stats for any agent' and enumerates specific outputs (total volume referred, commission earned, pending payout amount, number of referred agents). This distinguishes it from sibling tools like flipr_referral_leaderboard (which is for leaderboards) and flipr_referral_link (which is for links).
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 for individual agent referral stats ('any agent') but does not explicitly compare it to alternatives or state when not to use it. It lacks a clear 'use this instead of X' directive, so the usage context is only implied.
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.