get_sentiment

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

With no annotations provided, the description carries full burden. It transparently describes the output format, sources (listing specific English and Chinese outlets), and coverage skew (US large-caps, Taiwan semis). It does not mention any destructive behavior or side effects, but as a read-only tool, this is acceptable. Lacks mention of rate limits or authentication needs.

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?

The description is concise and dense, covering purpose, output, sources, and usage in a few sentences. It is front-loaded with the main action. However, the 'Useful for' list could be integrated into a more structured format.

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?

Given the low complexity (2 parameters, no output schema), the description is remarkably complete. It explains the return value details, sources, and usage contexts. No output schema is needed as the description sufficiently describes the response.

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?

Input schema coverage is 100%, so schema already documents parameters. The description adds value by clarifying ticker case-insensitivity, length limits, and coverage bias, as well as window_hours default and max. This goes beyond the schema 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?

The description clearly states the tool's purpose: get aggregated financial news sentiment for a single stock ticker. It specifies the output details (score range, confidence, article count, distribution, and latest articles) and sources. This distinguishes it from siblings like get_sentiment_batch (multiple tickers) and compare_languages (language comparison).

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?

The description includes a 'Useful for' section with concrete scenarios: gauging market mood before a position, monitoring post-earnings sentiment, explaining price moves. This provides clear usage guidance. However, it does not explicitly state when not to use the tool or mention alternatives beyond sibling tool names.

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