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Get Trump Stock Mentions

get_trump_mentions
Read-onlyIdempotent

Retrieve stock tickers mentioned by Donald Trump, with sentiment and ROI since the mention. Returns paginated results.

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of results per page (1–50, default 25)
cursorNoPagination cursor (offset)
searchNoCase-insensitive search over the mention's ticker
sort_byNoField to sort by (default: mention_date)
sort_dirNoSort direction (default: desc)
sentimentNoFilter by mention sentiment

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, covering the safety profile. The description adds genuinely new context — that results are paginated and include sentiment plus ROI since the mention — but says nothing about result volume, freshness, or how ROI is computed. Adequate but thin on top of 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero waste, with the core capability stated first and the pagination caveat second. Nothing to trim.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six optional filter/sort params and no output schema, the description covers the returned fields and pagination adequately, but omits what the agent most needs: how this differs from the two sibling trump_mentions tools and what the mention record actually contains beyond sentiment and ROI.

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% with defaults and enums documented per parameter, so the schema carries the semantics. The description only echoes that sentiment and ROI are present; it adds no meaning about how search, sort_by, or cursor interact with the returned data.

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 uses a specific verb and resource — retrieves stock tickers mentioned by Donald Trump — plus the enrichment fields (sentiment, ROI since mention). It stops short of distinguishing itself from the closely-named siblings get_trump_mentions_holdings and get_trump_mentions_performance, which is the main ambiguity an agent faces here.

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 statement of when to use this versus alternatives, and the sibling list contains three near-identical 'trump_mentions' tools. Nothing tells the agent whether this is the raw mention feed while the others aggregate holdings/performance — the agent must infer that from the titles alone.

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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