analyze_sentiment_trend

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

With no annotations provided, the description carries the full burden and delivers comprehensive detail: read-only, stateless, idempotent, authentication requirements, rate limits (free 10/day), error handling, and data privacy. The 'Behavioral Transparency' section is thorough and leaves no ambiguity about side effects or safety.

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 well-structured with clear sections (Behavior, When to use, Args, Behavioral Transparency) and front-loads the purpose. However, there is redundancy between the 'Behavior' and 'Behavioral Transparency' sections that could be merged for conciseness.

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 output schema exists, the description does not need to detail return values. It covers authentication, rate limits, errors, and idempotency. However, it lacks specificity about what 'sentiment trends' analysis actually produces (e.g., scores, time series) and the 'When to use' section is too generic to fully contextualize the tool's role among siblings.

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 0%, so the description must add meaning beyond parameter names. The 'Args' section only restates the names with generic phrases ('The competitor name to analyze or process') and adds no further semantics like format, constraints, or behavior. This fails to compensate for the missing schema descriptions.

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 starts with 'Analyze sentiment trends' which gives a clear verb and resource, but then becomes generic ('structured analysis or classification of inputs against established frameworks or standards'). It does not explicitly differentiate from sibling tools like get_mentions or get_competitor_comparison, leaving the specific purpose somewhat vague.

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 explicit 'When to use' and 'When NOT to use' sections, but the advice is generic ('structured analysis or classification') and does not reference sibling tools or provide specific context for when to choose this tool over alternatives. The exclusion ('not for real-time production decision-making') is helpful but still lacks comparative guidance.

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