fund_graded_fund_daily_em

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the description's added context is limited to the specific time window (current trading day) and return type (pandas.DataFrame). There's no contradiction, but no deeper behavioral details are provided.

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 compact and front-loaded with purpose, followed by a source URL and return docs. The URL line adds provenance but is not strictly necessary for tool invocation; otherwise every line earns its place.

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 read-only tool, the description covers what it returns and the data type, but lacks details about the DataFrame's columns, row granularity, or potential emptiness on non-trading days. The URL provides additional context but doesn't substitute for missing output structure.

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?

With zero parameters, the schema describes everything needed. The description adds no param semantics because none exist; baseline 4 applies, as there is nothing to clarify or compensate for.

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 returns all graded fund net values for the current trading day, naming the resource and data source. However, it doesn't explicitly distinguish this from sibling tools like fund_graded_fund_info_em, leaving the 'daily' vs 'info' distinction implicit.

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 via the data scope ('current trading day'), but provides no explicit guidance on when to use this tool versus alternatives. It doesn't mention when not to use it or suggest a better sibling for other scenarios.

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