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Quantral Stock Sentiment

Company mentions

get_company_signals
Read-onlyIdempotent

Use this when the user wants the evidence behind a company's score: the individual posts and filings it was built from. Returns the most recent tracked mentions (up to 50), newest first, each with its sentiment, an excerpt, the source and the author's track record where known. A Reddit thread is one mention: the post, with the replies that mention the company nested under it in comments (commentCount gives the total). An item marked threadOnly is a post that did not mention the company itself; only its comments did, so it carries no sentiment of its own. Pass month (YYYY-MM) to scope to one calendar month. Korean broker research notes (sourceType telegram) add a broker line with the firm's rating and target price; they are context only and do not feed the score. Excerpts are opinions of their authors, not facts or advice; attribute them when quoting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthNoUTC calendar month as YYYY-MM. Omit for the most recent mentions.
tickerYesTicker symbol, for example AAPL.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description adds substantial behavior: result cap of 50, newest-first ordering, per-item fields (sentiment, excerpt, source, author track record), Reddit thread nesting with commentCount, the threadOnly edge case, broker-note handling, and an attribution caveat. This is well beyond what structured fields convey.

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?

Long but front-loaded: the usage trigger and return shape come first, followed by the edge cases. Every sentence carries substantive information and none is filler, though the density of thread/broker detail makes it heavier than strictly necessary.

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?

With no output schema, the description carries the full burden of describing returns and does so thoroughly: item shape, ordering, cap, nesting semantics, and the threadOnly anomaly. It also flags that excerpts are opinions, not advice, which is important for correct downstream use.

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%, so both parameters are already documented in the schema. The description's note on month (YYYY-MM scoping to one calendar month) largely restates the schema rather than adding new syntax or constraints, so the baseline 3 applies.

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 (returns the individual posts and filings behind a company's score) and immediately distinguishes it from the sibling get_company_score by framing it as the underlying evidence. An agent can tell this apart from get_top_signals or get_company_recaps without opening a schema.

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

Usage Guidelines4/5

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

"Use this when the user wants the evidence behind a company's score" gives clear triggering context and implicitly routes against get_company_score. It does not explicitly name the alternative sibling or state when not to use it, so it stops short of full when/when-not guidance.

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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