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Crawlora MCP

polymarket_activity_trades

Read-only

Fetches credential-free public Data API trade rows scoped by one market condition id. A valid public market with no recent matching public trades can return an empty trades array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum trades to return, default 50, maximum 100.
marketNoOptional market condition id. When set, returns trades for that market.
offsetNoResult offset, default 0, maximum 10000.
event_idNoOptional Polymarket event id. When set, returns trades for that event.
taker_onlyNoFilter to taker trades. Allowed values: true, false. Default true.
filter_typeNoActivity amount filter type. Allowed values: CASH. Default CASH.
filter_amountNoMinimum filtered amount. Allowed values: 1, 5, 10, 100, 1000, 10000, 100000. Default 1.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful context beyond that: the API is credential-free (no auth needed) and a valid market with no matching trades returns an empty array, setting correct expectations for a common edge case. It stops short of noting rate limits or pagination behavior.

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?

Two tight sentences, front-loaded with the core action and followed by the empty-result caveat. No filler, though the phrasing is slightly dense.

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 an output schema present and annotations covering the read-only/open-world profile, the description needn't explain return values. It covers the key operational facts (no credentials, possible empty array) but omits guidance on parameter interaction (market vs event_id) for a 7-parameter tool.

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 description coverage is 100%, so the schema already documents limit, offset, market, event_id, taker_only, filter_type, and filter_amount with defaults and allowed values. The description adds nothing param-specific beyond the market-scoping framing, so the baseline 3 is appropriate.

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 states a specific verb and resource ('Fetches credential-free public Data API trade rows') and names the scoping key ('one market condition id'), so the agent knows exactly what it retrieves. It does not, however, differentiate itself from adjacent Polymarket readers like polymarket_public_data or polymarket_market_detail, which the huge sibling list makes relevant.

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

Usage Guidelines2/5

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

There is no explicit when-to-use guidance, no statement of when to prefer this over other Polymarket data tools, and no prerequisites. Worse, it says rows are scoped by 'one market condition id' while the schema also accepts event_id, leaving the agent to infer the real selection semantics.

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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