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Vike Data API

by io.vike
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Predict.fun Market Trades

predictfun_market_trades
Read-onlyIdempotent

One Predict.fun market's on-chain fills with the wallet behind each, newest first: ts (epoch ms), tx_hash, wallet, counterparty, role (maker/taker), side (BUY/SELL of token_id), outcome, size (shares), price (0-1), usd, fee. Returns {trades, next_cursor}. One row is one ORDER's fill, not one match: a match is a maker row per resting order hit plus one taker row for the order that took them (whose amounts are theirs added up), so add usd over ONE role, never both.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "market_id": "<market_id>"
    },
    "name": "predictfun_market_trades"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoRows (default 100, max 10000).
cursorNoA previous page's `next_cursor`, unchanged, to read the next page.
market_idYesThe Predict.fun market id (`market_id` from predictfun_markets). Required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnly annotations, it discloses the return shape ({trades, next_cursor}), ordering, units (epoch ms, 0-1 price, shares), and a genuine analytical trap: one row is one order's fill, so a match spans multiple maker rows plus an aggregated taker row, meaning usd must be summed over one role only. That is precisely the context an agent would otherwise get wrong.

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-loaded with purpose, then field list, then return shape, then the maker/taker caveat – nothing is filler. The final sentence is long and dense but every clause carries load-bearing semantics about aggregation.

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 properly compensates by enumerating returned fields, their units and pagination behavior. Minor gaps remain: nothing about empty results, error behavior, or whether fee/usd are signed for SELL rows.

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 limit, cursor and market_id are already documented in the schema. The description reinforces pagination ("next_cursor" as the cursor source) and notes market_id origin, adding modest confirmation rather than new meaning.

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 verb and resource – "One Predict.fun market's on-chain fills with the wallet behind each, newest first" – plus the exact columns returned. The "one market" scoping implicitly separates it from wallet-level siblings like predictfun_wallet_trades without needing the name spelled out.

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

Usage Guidelines3/5

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

Usage is implied by the scope (single market, paginated, newest first), and the market_id provenance from predictfun_markets is stated. However, there is no explicit when-to-use / when-not-to-use guidance and no named alternative for wallet-level or cross-market trade queries.

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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