get_equities_earnings_calendar

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

Beyond the annotations (readOnly, idempotent), the description discloses fallback behavior (live fetch on cache miss), date-window defaults, plan-specific coverage differences, and internal dependencies (daily_fetch sweeps). This adds substantial context for the agent about how the tool behaves in various scenarios.

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 long but well-structured with clear sections and bullet points. It front-loads the purpose and use cases, then dives into technical details. While some internal references (e.g., jquants-mcp#621) are niche, they don't detract significantly from clarity. It could be slightly tightened, but every part 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?

Given the tool's complexity (plan differences, fallbacks, multiple query modes) and the presence of an output schema, the description covers all necessary context: parameter semantics, plan limitations, default behavior, and edge cases (cache misses). It is complete for an agent to decide when and how to use it.

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 the description fully compensates by explaining the date format (YYYYMMDD or YYYY-MM-DD), code format (5 digits, trailing 0 padding), and the behavior when omitted (latest data for date, accumulated search for code). This is essential for correct invocation.

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 finds upcoming/past earnings announcement dates (決算発表日) and provides a list of query phrases, but it does not explicitly differentiate it from sibling tools like get_earnings_this_week or get_earnings_results_this_week, relying on the name and usage examples to distinguish.

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?

Provides explicit usage guidance: lists query phrases (決算発表, earnings calendar, etc.), pairs with get_markets_short_sale_report for specific screening, and explains plan-dependent behavior (Free vs Light+). This goes beyond a simple when-to-use by offering context and alternatives.

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