evaluate_signal_quality

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

With no annotations, the description carries the full transparency burden. It discloses that the tool 'does not claim the full live system has exactly this accuracy' and frames itself as a 'defensible evaluation layer,' which is valuable. However, it does not describe operational details like data sources, what it computes step-by-step, or whether it has any side effects.

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 compact and logically arranged: an opening purpose, important caveats, and parameter definitions. The three 'Important' bullet points are somewhat redundant, all conveying the same honesty message, but the overall length is reasonable and front-loaded.

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?

Given an output schema exists, return values are covered separately. The description covers purpose, limitations, and parameter meanings, but it lacks a clear explanation of what 'checkpoints' and 'hit evaluation' mean, and it relies on familiarity with the 'signal engine' and 'price-action core.' This makes it incomplete for a new user without additional context.

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 0%, so the description fully compensates by explaining each parameter: symbol is an 'NSE symbol', lookback_months is a 'historical window for checkpoints', and holding_days is a 'forward return horizon for hit evaluation'. This adds clear semantic meaning beyond the schema's bare titles and defaults.

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 calls the tool a 'Lightweight evaluation / proof layer for the signal engine's price-action core' and emphasizes honesty, but stops short of stating a concrete verb+resource (e.g., 'computes historical accuracy metrics'). It differentiates from siblings only through the 'honesty tool' framing, not through specific functionality.

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 description implies a use case ('before making accuracy claims') and positions itself as an honest proof layer, but it does not explicitly state when to use this tool versus alternative tools like get_signal_accuracy or check_signal_outcomes. No exclusions or alternative names are provided.

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