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get_market_commentary

Read-onlyIdempotent

Cached equities market sentiment snapshot.

Returns {overallSentiment, atmosphere, keyThemes, tailwinds, headwinds}.
Generated by TipRanks' AI pipeline with web search, refreshed every
~4 hours; this endpoint reads the cache only and does not trigger
regeneration. If no recent cache exists, returns
{"status": "unavailable"}.

The content is AI-generated commentary, not authoritative TipRanks
market data — present it as such to end users.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds substantial context beyond that: it reads a ~4-hour-old cache, does not trigger regeneration, returns a specific 'unavailable' status when no cache exists, and warns that content is AI-generated and not authoritative. These are non-obvious behavioral traits that materially affect how an agent should invoke and present the results.

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?

The description is four sentences, front-loaded with the core purpose. Every sentence serves a distinct role: what it is, what it returns, how/when it's generated, cache-only behavior, error case, and usage caveat. No filler or redundant restatement of the tool's name.

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, no-output-schema tool, this description is complete. It documents the return structure, the refresh interval, the cache-miss behavior, and the AI-generation caveat. The agent has everything needed to decide invoke, interpret results, and communicate them to end users.

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 has zero parameters and the schema properties are empty (coverage is trivially 100%). The description correctly adds no parameter noise. Given the 0-parameter baseline of 4, this score is appropriate; the description instead clarifies the output shape and cache behavior, which is more valuable here.

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?

The description opens with 'Cached equities market sentiment snapshot,' a specific verb+resource+qualifier that immediately distinguishes this from siblings like get_market_movers or get_market_performance. It also enumerates the exact return fields (overallSentiment, atmosphere, keyThemes, tailwinds, headwinds), leaving no ambiguity about its purpose.

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?

The description clearly establishes the context: this is a cache-only endpoint that never triggers regeneration and may return 'unavailable' if no cache exists. This implies it is suitable for quick, non-authoritative sentiment reads. However, it does not explicitly name alternative tools (e.g., get_investor_sentiment or get_market_performance) for cases where real-time or authoritative data is needed, so it stops short of full exclusion 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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TDQS

A3.8/5.0
Disambiguation3/5

Many tools have overlapping purposes, e.g. get_etf_analysis vs get_etf_forecast both provide ETF analyst consensus, get_etf_holdings vs get_etf_top_stocks both list constituents, and get_portfolio_overview vs get_portfolio_performance both return returns/performance. The detailed descriptions help, but the sheer number of similar tools creates ambiguity in selection.

Naming Consistency4/5

The set is largely consistent with a 'get_' prefix and descriptive nouns (get_stock_quotes, get_crypto_quote, get_dividend_history). Minor deviations include 'list_my_portfolios' instead of 'get_my_portfolios' and singular/plural variants like get_all_commodities_quotes vs get_commodity_quote, but the pattern remains predictable.

Tool Count1/5

With 71 tools, the count far exceeds the 50+ threshold described as an extreme mismatch. Even though the server covers a broad financial domain, such a large surface is overwhelming for an agent and includes many redundant or highly specific tools that could be consolidated.

Completeness5/5

The tool set provides comprehensive coverage of TipRanks data: quotes and historical data for all major asset classes, news, earnings and economic calendars, analyst and sentiment data, financial statements, technical analysis, options, portfolios, and screeners. There are no obvious dead ends for typical financial research tasks.

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