lookup_point_value

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

The description adds significant behavioral context beyond the annotations: it explains the behavior with no year (returns latest settled value per region × sector) and with year/quarter (returns quarterly time series). It also clarifies that values are typically less than NT$1. No contradiction with annotations, which already mark it as readOnly and idempotent.

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-structured: starts with the core function, explains the context, then parameter behavior, and ends with usage guidance and attribution. It is slightly verbose but each sentence serves a purpose. Could be trimmed slightly without losing meaning.

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 complexity of the NHI point value system, the description provides enough context for an agent to understand what the tool does and when to use it. It mentions the output (settled rates, quarterly time series) but not the exact format. Since there's no output schema, a bit more detail on the return structure would improve completeness, but it is adequate.

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?

All parameters have descriptions in the schema (100% coverage), so the description doesn't need to repeat them. However, it adds domain-specific context (e.g., 'floating' vs 'average' metric) and explains the interaction between year and quarter. This adds value beyond 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 states the tool's purpose: looking up Taiwan NHI floating point values, the settled per-point payment amount by region and sector. It explains the context of the global budget system and distinguishes the tool from sibling tools by focusing on a specific domain (point values) rather than other NHI lookups.

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 tells when to use the tool: 'Use when an agent needs to estimate actual reimbursement.' It also notes the official source for reference. While it doesn't explicitly state when not to use it or compare with alternatives, the use case is clear and actionable.

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