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calvernaz

Alpha Vantage MCP Server

by calvernaz

news_sentiment

Analyze market sentiment by fetching and processing news articles for specified stocks, enabling data-driven investment decisions through Alpha Vantage's financial data platform.

Instructions

Fetch news sentiment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickersYes
topicsNo
time_fromNo
time_toNo
sortNo
limitNo
datatypeNo
Behavior1/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers none. It doesn't indicate whether this is a read-only operation, what data sources are used, whether there are rate limits, authentication requirements, or what the output format might be. 'Fetch' implies retrieval but gives no insight into the tool's actual behavior beyond the basic action.

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 extremely concise at just two words, with no wasted language. While this represents severe under-specification rather than ideal conciseness, from a pure structural perspective it's front-loaded and contains zero redundant information.

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

Completeness1/5

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

For a tool with 7 parameters (one required), 0% schema description coverage, no annotations, and no output schema, the description is completely inadequate. It provides minimal information about purpose and zero guidance on usage, behavior, or parameters. This leaves the agent with insufficient context to effectively select or invoke this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description provides zero information about any of the 7 parameters, despite 0% schema description coverage. Parameters like 'tickers', 'topics', 'time_from', 'time_to', 'sort', 'limit', and 'datatype' are completely undocumented in both schema and description. The description doesn't even hint at what inputs are expected or their purposes.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Fetch news sentiment' is a tautology that essentially restates the tool name 'news_sentiment' with a generic verb. It doesn't specify what resource is being fetched (e.g., sentiment scores, articles with sentiment analysis), how the sentiment is calculated, or what format the results take. While it indicates a retrieval action, it lacks the specificity needed to distinguish it from potential alternatives.

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

Usage Guidelines1/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, constraints, or comparison to sibling tools (which appear to be primarily financial/technical indicators and data fetchers). There's no indication of appropriate contexts or scenarios for news sentiment analysis.

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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