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Vike Data API

by io.vike
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Predict.fun Market Detail

predictfun_market_detail
Read-onlyIdempotent

One Predict.fun market by market_id: the market (title, question, status, category, fees, and details, Predict.fun's own record of it), its outcomes (token ids, names, WON/LOST once resolved, each one's last price) and stats (24-hour and total USD volume, 24-hour matches and wallets, last_price of the first outcome, Yes). The 24 hours are whole fill hours ending with the newest hour built (up to ~1.5 h behind the live tape). An unknown id is an error.

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_detail"
  }
}

Input Schema

NameRequiredDescriptionDefault
market_idYesThe Predict.fun market id (`market_id` from predictfun_markets). Required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive behavior, but the description adds substantive details: the returned sections, resolution statuses, the whole-fill-hour 24h window, up to ~1.5h lag behind the live tape, and unknown-id error behavior. This is exactly the extra operational context needed beyond the annotations.

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 front-loads the operation and uses three compact sentences with no filler. The long parenthetical field inventory is dense but justified because there is no output schema; slightly run-on structure keeps it from a 5.

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?

For a one-parameter, read-only detail endpoint with no output schema, the description covers what is returned, how the 24h stats are defined, and how errors work. Nothing material for correct invocation appears to be missing.

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?

There is only one parameter and schema coverage is 100%, with the schema itself stating that `market_id` is required and comes from `predictfun_markets`. The description reinforces the identifier and notes that an unknown id is an error, but adds little syntax or format detail beyond the schema baseline.

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?

States that this returns exactly one Predict.fun market by `market_id` and enumerates the market metadata, outcomes, and stats. It is clearly a single-market detail lookup rather than a list/book/trades tool, though it never explicitly contrasts itself with a named sibling.

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?

The singular 'One market' plus required `market_id` imply use when you already have a market id and need full market data. However, it gives no explicit when-to-use guidance versus `predictfun_market_book` or `predictfun_market_trades`, and no exclusions, so guidance is only implied.

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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