get_correlation_matrix

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the price ('Price: $0.50'), which is useful context about cost implications. However, it doesn't describe rate limits, authentication needs, error conditions, or what happens with invalid inputs. The description states what the tool does but lacks operational details an agent would need.

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 appropriately sized and well-structured with clear sections (purpose, args, returns, price). Each sentence earns its place, though the 'Price: $0.50' could be integrated more smoothly. It's front-loaded with the core purpose, followed by necessary details without redundancy.

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 2 parameters with 0% schema coverage and an output schema present, the description does a reasonable job. It explains parameters well and states the return type ('Correlation coefficients between all token pairs.'), though the output schema would provide exact structure. However, as a data analysis tool with no annotations, it should ideally mention data sources, accuracy limitations, or computational constraints for better completeness.

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 compensate. It successfully explains both parameters: 'tokens: List of token addresses or symbols to analyze' and 'timeframe: Analysis period. Options: 1d, 7d, 30d, 90d.' This adds crucial meaning beyond the bare schema, including format details and valid options. The default value for timeframe is mentioned in the schema but not the description, keeping this from a perfect score.

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 correlation matrix between multiple tokens.' It specifies the verb ('Get') and resource ('correlation matrix'), and clarifies it analyzes relationships between tokens. However, it doesn't explicitly differentiate from sibling tools like 'get_risk_metrics' or 'get_trading_signal' that might also involve token analysis.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or comparisons to sibling tools like 'get_risk_metrics' or 'optimize_portfolio' that might offer overlapping functionality. The price information hints at a paid service but doesn't clarify usage scenarios.

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