strategy_compare_metrics

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, and idempotentHint=false, so the safety profile is mostly covered. The description adds useful behavioral context by saying it computes both absolute and relative changes and does not infer causation or investment merit. However, it does not describe the expected input shape, error behavior, or result structure beyond the output categories.

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 definition is a single front-loaded sentence with no redundant wording. It states the operation, the outputs, and an important limitation efficiently.

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 nested object parameters, 0% schema description coverage, and absence of an output schema, the description is too thin. It names the high-level comparison but does not specify the metric object format or return shape, leaving an agent without enough detail to invoke the tool confidently beyond passing two arbitrary objects.

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%, and both parameters are untyped nested objects with no property-level documentation. The description only implies that baseline and candidate are the two metric objects being compared; it does not explain what keys or metric fields are expected, how missing fields are handled, or how the 1000-property limit applies.

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 states a specific verb and resource: compare two supplied metric objects. It also names the computed outputs, absolute and relative changes, and clarifies a boundary: it does not infer causation or investment merit. It is clear, but it does not explicitly distinguish itself from nearby metrics-oriented siblings such as research_equity_metrics or research_rank_results.

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 this is for comparing two metric snapshots, but it gives no explicit when-to-use or when-not-to-use guidance. It does not name alternatives or explain whether this is preferable to strategy_scan, strategy_sweep, or research_equity_metrics for particular tasks.

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