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Coinversaa

Coinversaa Pulse

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by Coinversaa

Builder Retention

builder_retention
Read-onlyIdempotent

Check monthly user retention for any Hyperliquid builder from a 0x builder address. See how each wallet cohort behaves over time to identify retention or churn.

Instructions

Monthly retention matrix for a builder's users (takes only the 0x-hex builder address — no other parameters): wallets are cohorted by the calendar month (YYYY-MM, UTC) of their first builder-fee order via this builder, and each cohort's activeWallets[k] counts wallets still active k months later, where 'active' = placed at least one builder-fee order that month (index 0 = the cohort month itself = newWallets). Covers the last 12 calendar months, oldest cohort first. Measured on the ORDERS plane — the order need not fill — so counts can exceed the attributed-fill user counts on builder_cohorts/builder_overlap; see the response's dataNotes for the attribution caveat. Use for 'does builder X retain users month over month, or churn them?'. Requires Pro tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
builderYesBuilder address (0x...)
useToonFormatNoReturn data in compact toon format (default: true). Set to false for standard JSON.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv0.11.1
    • changedInput schema / properties / builder / description
      Previous value: -"Builder address (0x...) — the fee-receiving address a frontend/bot/dex registers on Hyperliquid"New value: +"Builder address (0x...)"
  2. Addedv0.11.0

TDQS

A4.4/5.0
Behavior5/5

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

Even with strong readOnly/idempotent annotations, the description adds substantial behavioral detail: cohorting by first builder-fee order, the definition of active, index 0 = newWallets, 12-month window with oldest-first ordering, and the ORDERS-plane caveat. It also flags dataNotes and the Pro tier requirement.

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?

The description is dense but every substantive element earns its place, and the key purpose is front-loaded. It loses one point for the inaccurate parenthetical and for packing definitions into a long run-on sentence, though this is more a clarity issue than bloat.

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

Completeness5/5

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

With no output schema available, the description supplies the essential response semantics: cohort key, activeWallets[k], newWallets, time range, ordering, and dataNotes caveat. An agent receives enough context to call the tool correctly and interpret the returned retention matrix.

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

Parameters2/5

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

Schema coverage is 100%, so a baseline of 3 would normally apply, but the description's emphatic claim 'no other parameters' contradicts the schema's optional useToonFormat parameter. This is actively misleading for invocation despite the useful note that the builder must be a 0x-hex address.

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?

The description names a specific deliverable ('Monthly retention matrix') and the exact question it answers, and differentiates itself from builder_cohorts/builder_overlap by calling out the ORDERS-plane measurement. The distinction is enough for an agent to select it over the sibling retention-related tools.

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?

The description explicitly frames the intended use as retention/churn analysis and points out when its counts will differ from the attributed-fill metrics on builder_cohorts/builder_overlap. This gives clear routing guidance to siblings without further inference.

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

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