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Builders leaderboard (revenue, volume, users by window)

flowscan_builders_leaderboard
Read-only

Rank Hyperliquid builders by revenue, volume, new users, total users, or average revenue per user across 1d, 7d, 30d, 90d, or all-time windows.

Instructions

The /builders 'Builder Arena': ~1800 builders ranked by one metric over a FIXED window (1d/7d/30d/90d/all_time): revenue, volume (USD), new_users, total_users or avg_revenue_per_user_all_time (last two all-time only). Compact rows (rank, id, name, category, value, that metric's windows, all-time revenue, users); full=true for all metrics. For arbitrary ranges like 'last 45 days' use flowscan_builder_revenue; flowscan_hip3_builders ranks by HIP-3 volume only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNoReturn every metric and window per builder (default false).
limitNoMax list items (default per tool).
fieldsNoPaths to keep, relative to `data` (list tools: each row); misses go to _fieldsNotFound.
metricNoSort metric (default revenue).
offsetNoList items to skip.
searchNoFilter by builder id/name substring.
windowNoDefault 7d (all-time-only metrics ignore it).
categoryNoCategory substring (wallet, copytrading, ...).
minUsersNoMin all-time users (default 0); useful for avg_revenue_per_user_all_time.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and open-world nature are covered. The description adds useful context beyond annotations — approximate scale (~1800 builders), the fixed-window limitation, and the shape of returned rows (rank, id, name, category, value, windows, all-time revenue, users) plus full=true behavior. It stops short of noting pagination behavior, but the return-shape disclosure is real added value.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the resource and ranking model before the routing alternatives; every clause carries information. It is dense and parenthetical-heavy, but there is little true filler, so it stays efficient without being wasteful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description compensates by describing the returned row fields and the full=true variant, and it resolves the main ambiguity (fixed vs arbitrary windows) by pointing to the correct sibling. Coverage of pagination and default limits is left to the schema, which documents it, so completeness is strong though not exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real semantics: the window set is FIXED (1d/7d/30d/90d/all_time), new_users/total_users/avg_revenue_per_user_all_time are all-time only, and full=true returns all metrics. This clarifies cross-parameter behavior the schema cannot express on its own.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific resource and operation ('Builder Arena' leaderboard of ~1800 builders ranked by one metric) plus scope constraints (fixed window, list of metrics). It explicitly distinguishes itself from the two most confusion-prone siblings by name. An agent can identify what this returns without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit routing rules: arbitrary ranges like 'last 45 days' go to flowscan_builder_revenue, and flowscan_hip3_builders is for HIP-3 volume only. It also states the fixed-window constraint that determines when this tool is the right choice. Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.