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export_trade_log

Export wallet transaction events. API-key-only, 2,500-credit export of the canonical role-aware transaction classifier. format=csv (default) returns a cached signed download URL for up to 366 days. format=json returns inline peerlytics.transaction-events.v2 data for up to 31 days. Stable event ids, classifications, signed USDC amounts, fiat values, role, counterparty, references, attribution, and flags are shared across both formats. x402 is not supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesInclusive UTC range end. Date-only input closes at 23:59:59.999.
fromYesInclusive UTC range start. Date-only input opens at 00:00:00.000.
formatNoDelivery format. JSON is inline and capped at 31 days.csv
walletYesWallet to classify as maker, taker, or self.

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly. It discloses auth requirements, credit cost, cached vs inline delivery, retention limits, the shared data contract, and an unsupported protocol — far more behavioral context than typical.

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?

Four dense sentences with no filler, front-loaded with the core purpose before moving to format and data details. Every sentence contributes a distinct, useful fact, and the structure makes the key format/cost/auth tradeoffs immediately visible.

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?

Despite lacking an output schema, the description covers the response shape (signed URL vs inline JSON), retention periods, the shared field set, authentication constraints, and cost. An agent has enough information 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.

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. The description adds real value beyond the schema by explaining what format=csv vs format=json actually returns (cached signed URL vs inline data) and by listing the shared fields across both formats.

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 opens with a specific verb and resource — 'Export wallet transaction events' — and immediately distinguishes this as an export tool rather than a simple get/list tool. It further clarifies the canonical role-aware classifier and format-specific outputs, making its purpose unambiguous relative to the numerous sibling tools.

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 clearly establishes context: API-key-only access, a 2,500-credit cost, and explicit rejection of x402. It implies this is for bulk or durable export rather than interactive queries, though it doesn't name specific alternatives or state when not to use it.

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.

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