analyze_market_trends

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

No annotations are provided, so the description carries full burden. It only states 'analyze' but does not disclose behavioral traits such as whether it has side effects, authorization requirements, rate limits, or if it triggers long computations. The description is insufficient to inform an agent about operational constraints.

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 a single sentence of 12 words, which is efficient and front-loaded. It avoids unnecessary details, but given the lack of parameter and usage information, the conciseness comes at the cost of completeness. Still, it earns a 4 for being well-structured and appropriately sized for the core purpose.

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?

While an output schema exists (reducing need to describe return values), the description does not explain what 'trends' entails or how the optional parameters affect results. It misses key contextual details like default behavior (e.g., credit_types=null means all) and output format, making it incomplete for effective tool invocation.

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%, meaning the input schema provides no parameter descriptions. The tool description does not mention the parameters 'time_period' or 'credit_types' at all, failing to add context about valid values, defaults, or behavior. This is a critical gap for correct parameter usage.

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 analyzes market trends across credit types using historical data. It uses a specific verb ('analyze') and resource ('market trends'), and distinguishes from sibling tools like 'analyze_portfolio_impact' which focuses on portfolio, and 'compare_credit_methodologies' which is comparison. However, it could be more precise about the output (e.g., what kind of analysis is produced).

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, complementary tools, or when not to use it. With multiple analysis tools available (e.g., analyze_portfolio_impact), the lack of usage context reduces its utility for agent selection.

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