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

No annotations are provided, so the description carries the full burden. It discloses the aggregation scope ('Covers every trade in the range') and defines the unusual `symbolDays` metric. As a read-only analytics tool, this is sufficient behavioral context, even though it doesn't discuss permissions or rate limits.

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?

Three dense, purposeful sentences: the first defines the output metrics, the second states the use case, and the third points to a relevant follow-up. Every clause earns its place with no filler.

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?

Without an output schema, the description compensates by naming the return metrics and the data scope. It could more explicitly describe the output shape, but an agent can infer per-playbook and per-strategy rows from the first sentence, and the schema covers the date parameters.

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%, so the baseline is 3. The description only references 'the range' and adds no format or semantic detail beyond what the schema already provides for startDate and endDate.

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 opens with a specific statement of what the tool reports: how each playbook has actually performed, with the exact metrics (trades, win rate, net P&L, fees, symbolDays). This clearly distinguishes it from sibling performance tools by its per-playbook and per-strategy focus.

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 explicitly gives a when-to-use framing: 'This is the tool for "is this playbook working for me"' and for checking a plan against its record. It also suggests a follow-up tool (get_symbol_reviews filtered to the playbook), though it doesn't explicitly list when-not-to-use alternatives.

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