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peerlytics

by xyz.peerlytics

get_maker_history

Maker history metrics. Without window params: lifetime aggregates and a recent window of 30 newest intents. With from/to/range: every metric recomputes for the period.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoWindow upper bound (exclusive). ISO-8601 or unix-seconds. Defaults to `now` when omitted but `from` is supplied.
fromNoWindow lower bound (inclusive). ISO-8601 (`2026-04-01T00:00:00Z`) or unix-seconds. Optional when `range` is supplied.
limitNoMax number of results to return.
rangeNoUnified date-range shortcut shared across analytics + explorer endpoints. Hard cap: 400-day window. When set, takes precedence over `from`/`to`. Legacy values (`3mtd`, `q1`-`q4`, `custom`) were retired on 2026-04-30; use the explicit shortcuts below.
cursorNoPass the previous page's `next_cursor` to walk forward without offset drift. This is the supported pagination path on every list endpoint.
offsetNoDeprecated. Use `cursor` instead — offset pagination is fragile under concurrent writes and slow at scale. Still accepted for backwards compatibility while integrators migrate.
addressYes

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the behavioral difference between providing window parameters and omitting them, including the default recent window of 30 intents. This is good transparency for a read-only tool.

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

Conciseness5/5

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

The description is two sentences, front-loading the core function and immediately clarifying behavior. Every word earns its place; there is no redundancy.

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?

Given 7 parameters, high schema coverage, and no output schema, the description covers the essential behavioral context. It explains the two main usage modes and the effect of parameters. It does not detail return values, but that is acceptable without output schema.

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

Parameters3/5

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

Schema coverage is 86%, high. The description adds value by explaining the collective effect of window parameters (from/to/range) on metric recomputation. However, individual parameter semantics are well-covered by the schema, so the description provides modest additional meaning.

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

Purpose4/5

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

The description clearly states the tool returns 'maker history metrics' and explains behavior with and without window parameters. It is specific but does not explicitly differentiate from sibling tools like get_maker or get_taker_history.

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

Usage Guidelines4/5

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

The description explains when to use window parameters vs not, noting that without them it returns lifetime aggregates and a recent window, and with them metrics recompute. It does not provide explicit when-not-to-use or alternative tools.

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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TDQS

C2.8/5.0
Disambiguation3/5

Most get_* and list_* tools target distinct domain entities, but several high-level analytics endpoints overlap in purpose (get_analytics_summary, get_protocol_overview, get_market_summary, get_timeseries, get_leaderboard), and pairs like get_deposit/get_deposit_context and get_vault/get_vault_analytics create close boundaries. The descriptions clarify the differences, but an agent would need to read carefully to avoid misselection.

Naming Consistency5/5

The tool set follows a strong verb_noun pattern: get_ for single-entity or detail views, list_ for collections, plus explicit action endpoints like export_trade_log, plan_routes, and search_explorer. All names are snake_case and predictable, with no mixing of conventions.

Tool Count3/5

28 tools is on the heavy side for an MCP server, even for a broad analytics domain. Most tools map to real entities, but the surface is padded by overlapping summary/analytics endpoints and separate detail, context, and analytics variants for the same resources.

Completeness4/5

The server provides broad read-only coverage of the protocol domain: deposits, intents, makers, takers, vaults, delegates, verifiers, platforms, integrators, orderbook, routes, activity, and search. Minor gaps such as no list_vaults or list_integrators are workable via search/get endpoints, and mutating operations appear out of scope for an analytics-focused server.

Resources