get_equities_bars_daily

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description reveals important behavioral details: MktCap is null for ETF/ETN and non-trading days, ExRT encodes specific corporate action types, and data retention varies by plan. It also notes that date-only queries are slow and API fallback on cache miss, which are not conveyed by annotations alone.

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 dense yet well-organized, with clear sections for overview, usage, data nuances, plan limitations, and argument definitions. Every sentence adds value—no filler—and the structure makes it easy to scan, despite the length.

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 (4 optional parameters, multiple usage modes), the description covers all critical aspects: parameter combinations, special field behaviors (MktCap, ExRT), plan retention limits, performance warnings, and alternatives. The presence of an output schema means return format details are not needed, so the description is complete.

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 coverage is 0%, but the description fully compensates by defining each parameter's format and semantics (e.g., code: 5-digit stock code, date: YYYYMMDD or YYYY-MM-DD). It also explains the interaction between parameters (code only → full history, code+range → period, date only → all stocks), which is crucial for correct usage and not derivable from the schema.

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 identifies the tool as providing per-stock or per-day OHLC bars for equities, with a specific verb and resource. It also lists the exact query types it supports (株価, 日足, OHLC, etc.), making it distinct from sibling tools like get_equities_bars_minute or get_indices_bars_daily.

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 explicitly states what queries to use this tool for and points to an alternative for bulk downloads: 'For multi-stock bulk downloads use get_bulk_list'. It also explains parameter combination patterns (code only, code+range, date only), giving clear context on when this tool is appropriate.

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