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

Beyond the read-only, idempotent, non-destructive annotations, the description discloses the returned content in detail: real-days-only numbers, paper record, full back-test, benchmark scorecard, modelled costs, turnover, and second-source check. It also warns that the back-test never ranks and that the record is labelled hypothetical, which is valuable behavioral context.

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 purpose is front-loaded, but the description is a dense, long run-on sentence with multiple embedded clauses. It is informative yet less scannable than it could be, and it repeats the slug source already present in the schema.

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?

With no output schema, the description does a strong job explaining the major sections and caveats of the returned record. It does not describe the exact response shape or field-level structure, but it is complete enough for an agent to understand what calling the tool will yield.

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 schema already has 100% description coverage and states that the slug comes from strategy_list. The description repeats that source but adds no syntax, format, or validation detail 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 identifies a specific resource — one Strategy Lab strategy's record — and clarifies that it is labelled hypothetical and includes both paper and back-test data. It names strategy_list as the source of the slug, but it does not explicitly distinguish itself from other strategy-related siblings such as strategy_signals.

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 gives clear workflow guidance: take a slug from strategy_list and read the paper record before the back-test. It does not state when to use this instead of alternatives like strategy_signals or compare_to_benchmark, so some routing inference remains.

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