detect_drift

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

With no annotations provided, the description carries the full burden. It discloses the CUSUM formula (S_i = max(0, S_{i-1} + x_i - omega)), the drift threshold (S_i > 5 * std(sequence)), and the output of monotonic progress (is_improving, is_stalling, is_declining). However, it does not explicitly state the return format or side effects (e.g., read-only), though the analysis-oriented nature is clear.

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 well-structured: it begins with a clear purpose, then provides a required input format example, then the formula, then optional fields. It is somewhat long but every sentence contributes, and it is front-loaded with the key information.

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 should explain what the tool returns. It mentions 'reports monotonic progress' and lists the fields, and states when drift is detected, but it does not provide the exact output structure (e.g., a JSON object with drift_detected, is_improving, etc.). The context parameter is also complex, but the description gives only a high-level hint. Given the complexity, this is a notable gap.

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 adds a concrete example with values, notes the default for drift_sensitivity (0.5), and explains context's purpose (escalation and stall detection). However, the schema already provides detailed descriptions for all parameters, so the description adds marginal value 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 starts with 'Detect drift in a numeric sequence using CUSUM (Cumulative Sum) analysis with monotonic progress tracking.' This clearly states the specific verb (detect), resource (numeric sequence), and method (CUSUM), and distinguishes it from sibling tools like validate_confidence and check_numeric_claims, which focus on validation rather than drift detection.

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 provides a required input format example and explicitly notes optional fields (drift_sensitivity, context) with their defaults and purpose. It clearly implies when to use it (for drift detection in numeric sequences) but does not explicitly mention alternatives or exclusion scenarios. This is clear context without formal exclusions.

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