run_walk_forward_test

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

With no annotations provided, the description must disclose behavioral traits, but it only says 'testing' which implies a non-mutating operation. It does not state whether the tool is read-only, whether it fetches or modifies data, what it returns, or any side effects. For a tool that performs optimization, the lack of behavioral context is a significant gap.

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 a single concise sentence that front-loads the key action ('Walk-forward optimization testing') and states the purpose without any filler. It is efficient and scannable, with every word contributing meaning, so it earns a perfect score for conciseness.

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?

Despite a well-described schema, the tool has no output schema and no annotations, and the description is too minimal to convey the full operational context. It doesn't explain the mechanics of walk-forward testing (e.g., rolling window behavior), data source implications, or what the result looks like. Given the tool's complexity (6 parameters), this short description leaves the agent underinformed.

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 input schema descriptions cover all 6 parameters with clear definitions (e.g., 'Step size for rolling window in days', 'In-sample optimization period in days'), achieving 100% coverage. The tool description adds no parameter-specific meaning, but it doesn't need to since the schema already provides adequate semantics. This matches the baseline for high schema coverage.

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 identifies a specific function: walk-forward optimization testing with the goal of validating strategy robustness over time. It uses a specific verb ('testing') and resource ('strategy robustness'), and the term 'walk-forward' differentiates it from general backtesting siblings. However, it does not explicitly distinguish itself from related tools like run_backtesting_analysis or run_strategy_comparison, so it falls short of a 5.

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 phrase 'to validate strategy robustness over time' implies a use case for time-series validation, but the description offers no explicit guidance on when to choose this tool over siblings or when not to use it. It does not mention alternatives or exclusions, making usage largely implied rather than clearly instructed.

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