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Prediction Market X Sentiment

Sentiment change for a market

get_sentiment_shift

Paid (see get_pricing). Change in X sentiment for a market question since its previous score, with both timestamps and the catalyst.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesA Polymarket or Kalshi market question in plain words, e.g. 'Will the Fed cut rates in October 2026'. Up to 200 characters.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
errorNoSet when a spend cap blocked the call
shiftNo
acceptsNo
catalystNo
questionNo
price_usdNo
score_nowNo
scored_atNo
how_to_payNo
score_beforeNo
prior_scored_atNo
payment_requiredNoTrue when no payment was made; accepts and how_to_pay say how to pay

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

The annotations declare a non-read-only, non-idempotent, open-world operation, and the description's only added behavioral signal is the cost notice pointing at get_pricing. It does mention the returned timestamps and catalyst, but that overlaps with the existing output schema rather than disclosing 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 short sentences with no padding, and the cost caveat is front-loaded so an agent sees it before planning the call. Slightly telegraphic phrasing ("Change in X sentiment") costs a little clarity.

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?

For a one-parameter tool with a full output schema and annotation coverage, the definition covers purpose, cost, and output shape adequately. The missing piece is routing guidance relative to get_market_sentiment, which is a minor gap given the otherwise simple surface.

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?

With schema description coverage at 100%, the schema already documents the single q parameter including format and length limits. The description adds only "for a market question," which is weaker than the schema text, so the baseline 3 applies.

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 gives a specific verb (change in) and resource (X sentiment for a market question) plus scope (since its previous score). It is clearly differentiable from the current-snapshot sibling get_market_sentiment, though it never names that sibling explicitly.

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?

"Paid (see get_pricing)" tells the agent a precondition exists, but there is no explicit when-to-use vs when-not, and the obvious alternative (get_market_sentiment for a current snapshot) is not named. Usage is only implied by "since its previous score".

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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