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

The description explicitly states that it reads data and explains what happens when a note is missing or an outcome is unsettled, framing them as unavailable evidence rather than zero. This aligns with the readOnlyHint and provides transparent expectations about behavior.

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 concise and well-organized into three short sentences. It covers purpose, usage, and interpretation without unnecessary fluff, though the final sentence about the disclosed rule could be seen as slightly tangential.

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?

The description provides enough context for the tool to be understood independently, including its inputs and behavior. It does not explicitly reference sibling tools, but the description of the output and its non-stock-pick nature gives sufficient context for an agent to distinguish when 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?

The only parameter, date, is described with its format (YYYY-MM-DD) and its purpose (selects a published session). This is sufficient for an agent to understand how to use it, even though the schema provides little detail.

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 that the tool reads the published daily research, its selection rule, and settled-note tally. It also contrasts the note with a stock-pick list, making the purpose unambiguous and distinct from the sibling tools.

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?

It provides practical usage guidance by indicating that no arguments are needed and that an optional date selects a specific published session. It also clarifies how to interpret missing or unsettled data, though it does not explicitly compare against market_state or research_quality.

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