analyze_news_sentiment

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

No annotations present, so description carries full burden. Mentions 'aggregate sentiment counts' but lacks details on sentiment categories, calculation method, recency of news, or output format. Does not disclose if counts are raw or normalized.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

Two sentences, front-loaded with purpose, and clear. Though very concise, it wastes no words. Slightly under-specified but efficiently structured.

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

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

For a one-parameter tool with no output schema, the description should provide enough behavioral context. It fails to explain the exact output, scope of 'recent', or sentiment categories. Agent may need additional info to use correctly.

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

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

Schema has 0% coverage with no description for the 'symbol' parameter. The description does not explain that symbol is required or how it is used, leaving the agent to infer from the parameter name alone.

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

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

Clearly states it aggregates sentiment counts for a symbol's recent news. Distinguishes from fetch_latest_news (for nuance) and get_market_sentiment (market-wide).

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

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

Explicitly advises when to use alternative tools: fetch_latest_news for nuances and get_market_sentiment for market-wide read. Provides clear context for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.