run_walk_forward

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

Adds behavioral details beyond annotations: 'Long-running: up to a 600-second timeout; reports progress to capable clients'. Annotations are neutral (readOnlyHint=false, destructiveHint=false), and description does not contradict them.

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 efficient sentences: purpose, defaults/workflow, runtime. No redundant information. Every sentence adds value.

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?

Output schema exists, so return values need not be described. Description covers runtime and workflow context. Minor gap: lacks mention of prerequisites like having run optimization first (though implied by workflow).

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?

With 0% schema coverage, description only provides defaults for two optional parameters ('windows defaults to 5, metric to sharpe_ratio'). No explanation of required parameters symbol and strategy_id. Insufficient compensation for schema gaps.

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?

Description clearly states verb 'Run' and resource 'walk-forward optimization for symbol', with explicit purpose 'out-of-sample robustness check'. Distinguishes from siblings like run_backtest and run_optimize.

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 states when to use: 'Run it after run_optimize to compare in-sample vs out-of-sample behaviour (the optimize_and_verify workflow)'. Provides clear usage context, though does not list all when-not scenarios.

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