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

With no annotations, the description carries the full burden and does well by disclosing the row semantics and the key omission behavior ('Days with no trades are omitted'). It could additionally mention sort order or date inclusivity details, but these are minor for a simple read tool.

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?

Two tight sentences lead with the output shape hands-on, then give usage context and an important caveat. No wasted words.

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 two-parameter retrieval tool with no output schema, the description sufficiently defines the row shapehog and the no-trade-day edge case. It is not explicitly stated whether rows are sorted chronologically, but this is a minor omission given how specific the rest of the description is.

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 100%, and the schema already documents both parameters as inclusive YYYY-MM-DD dates. The description does not add parameter-level semantics, but it does not need to because the schema fully covers it.

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?

States a specific resource ('one row per trading day') and lists the concrete fields it returns: net P&L, trade count, wins, losses, and fees. The warning against inferring daily activity from monthly totals clearly differentiates this from monthly-level 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?

Explicitly says to use this for frequency, overtrading, streaks, and day-to-day shaping of a month, and gives the negative guidance 'do not infer daily activity by dividing a monthly total.' This makes the intended use case unmistakable.

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