refresh_feature_data

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

Annotations already indicate destructiveHint, so the description adds value by detailing the behavior: full fetch from 2000 for new features, incremental update to today for existing ones. It also mentions 'force-update stale data,' giving context beyond the annotation's binary hint. No contradiction with annotations.

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 two sentences, front-loaded with the primary action, and includes all essential context without verbose filler. Every sentence contributes actionable guidance, making it highly concise and well-structured.

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?

For a tool with one parameter and an output schema, the description is complete: it covers data sources, behavior differences based on feature newness, and usage triggers. The output schema handles return value details, so no additional explanation is needed.

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 covers 100% of the parameter descriptions, including an example for the 'tickers' array. The description does not add meaning beyond the schema; it only reiterates 'specific tickers' in passing. Baseline 3 is appropriate since the schema does the heavy lifting.

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 states the tool's function: 'Fetch/update historical training data for specific tickers from Yahoo Finance or FRED.' It uses a specific verb and resource, and distinguishes itself from sibling tools like add_feature by explicitly positioning itself as the refresh step after adding features.

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 gives explicit when-to-use guidance: 'Use this after add_feature, or to force-update stale data.' It also clarifies the difference between full fetch for new features and incremental updates for existing ones, eliminating ambiguity about selection.

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