get_valuation_ranking

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

Annotations already cover read-only/idempotent/non-destructive. The description adds meaningful context: cache-only behavior, supported plans, exclusion of net-loss and negative-book stocks, and the disc_months stale-financial filter. Slightly held back from 5 because it doesn't mention potential output size limits or response format variants, but output schema exists to cover that.

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-organized: it starts with purpose, then use cases, exclusions, alternatives, plan support, and a structured Args list. Every sentence adds value, and the structure makes it easy to scan. No redundant fluff.

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 tool's complexity (8 optional params, many sibling tools), the description covers purpose, usage, alternatives, behavioral nuances, and parameter semantics. An output schema exists, so the lack of a return-value section is acceptable. The inclusion of plan restrictions and cache behavior adds operational 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%, yet the description fully documents all 8 parameters with defaults, allowed values, and behavioral meaning (e.g., ascending order, min/max filters, market options, sector codes, disclosure-age cutoff). This completely compensates for the schema's lack of parameter 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 clearly states the tool ranks listed stocks by PER or PBR valuation multiple, with specific examples of intended use cases and metrics. It also distinguishes itself by naming alternative tools for related but distinct purposes.

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?

Explicit guidance on when to use this tool (for 割安株, PER/PBR ranking, screening) and when not to use it (use get_sector_briefing for sector medians, get_stock_briefing for single stocks, get_dividend_yield_ranking for dividend yield). This is exactly the kind of direct alternative mapping the dimension asks for.

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