Valuation History

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

Annotations already declare the tool as idempotent, read-only, and non-destructive. The description adds value by detailing the return structure (metrics with timestamp/value pairs) and its purpose (long-term percentile analysis), providing useful behavioral context beyond the annotations.

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 two sentences: one for purpose, one for return structure. Front-loaded with the action and resource, no superfluous words. Every sentence adds value.

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?

For a simple one-parameter tool with an output schema and comprehensive annotations, the description is complete. It explains the return structure and purpose, leaving no gaps for the agent to infer.

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?

The single parameter 'symbol' has a clear description in the schema with an example. Schema coverage is 100%, so the description adds no additional meaning. Baseline score of 3 is appropriate.

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 verb 'Get' and the resource 'valuation history time series', specifying the exact metrics returned (pe/pb/ps/dividend_yield) and their structure for long-term percentile analysis. This differentiates it from sibling tools like 'valuation' (current snapshot) and 'valuation_comparison'.

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 historical valuation data but does not explicitly state when to use this tool over alternatives. However, the context is clear: it's for time series analysis, which guides selection among siblings. Missing explicit exclusions or alternative mentions.

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