analyze_sentiment

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

No annotations are provided, so the description carries full burden. It discloses the AI models used (Groq with NVIDIA NIM fallback) and output format, but does not discuss potential limitations such as rate limits, token caps, latency, or error handling for invalid inputs. It partially discloses behavioral traits but lacks comprehensive context.

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 highly concise with three well-structured sentences: first states purpose and input, second states output, third states technology. Every sentence is informative and earns its place, with no waste.

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 tool's complexity (AI-powered, two parameters, no output schema, no annotations), the description covers purpose, input, output, and underlying model. However, it lacks details on edge cases, precision of score, error handling, or additional constraints. It is nearly complete but has minor gaps.

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 description coverage is 100%, and the description adds value by clarifying that 'text' overrides the symbol news fetch and providing examples for 'symbol'. This enhances understanding beyond the schema, which is a baseline 3, so a 4 is justified.

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 it performs sentiment analysis on news text or recent news for a ticker, specifying the output format (Bullish/Bearish/Neutral/Mixed with 0-100 score and key factors). It distinguishes itself from siblings like 'summarize_news' and 'analyze_earnings' by focusing on sentiment, with clear verb+resource.

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 implies usage for sentiment analysis but does not explicitly state when to use this tool over alternatives (e.g., summarize_news, analyze_earnings) or when not to use it. It lacks explicit guidance on exclusions or prerequisites.

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