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Prediction Market X Sentiment

Daily market scores (free)

get_daily_scores
Read-only

Free. Latest daily X (Twitter) sentiment score for each prediction market we track (Polymarket), with the change since the previous day, the catalyst and the market's Yes price. For a fresh score on any other question use get_market_sentiment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
as_ofNoTime of the newest score
countNo
marketsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered; the description adds non-annotation context: cost ('Free'), data freshness ('latest daily', 'change since the previous day'), and the exact data shape returned. It does not mention rate limits, caching, or what happens for markets without a score, so it stops short of full transparency.

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?

Two sentences, front-loaded with 'Free.' and the core payload, then a single routing sentence for the alternative. Every clause carries information (cost, freshness, scope, fields, fallback) with no filler.

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 zero-parameter read tool with an output schema covering return values and annotations covering safety, the description supplies everything else an agent needs: cost, coverage universe, freshness semantics, and the sibling to use for anything outside that universe.

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?

The tool takes no parameters (0 of 0 required, 100% schema coverage), so there is nothing for the description to clarify and the baseline is 4. The description correctly describes the tool as operating over the whole tracked market set rather than implying optional filtering inputs.

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+resource ('Latest daily X sentiment score for each prediction market we track'), names the covered universe (Polymarket), and enumerates exactly what each record contains: change since previous day, catalyst, and Yes price. It also explicitly distinguishes itself from get_market_sentiment, so an agent can disambiguate without opening either schema.

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

Usage Guidelines5/5

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

Provides an explicit routing rule for the sibling tool: 'For a fresh score on any other question use get_market_sentiment.' The condition (any question outside the tracked markets) and the alternative are both stated, leaving nothing to inference.

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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