get_portfolio_analytics

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

Annotations declare readOnlyHint=true, and the description adds meaningful behavioral context: the backward-looking nature and the dependency on compute_betas. It also explains what the optional model_group_id does (factor attribution with examples). These details go beyond the annotation, though it doesn't describe error behavior or rate limits, which are not critical here.

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 front-loaded with the main purpose and keeps information compact. Each of the four sentences adds a distinct point: metrics/timeframes, backward-looking distinction, optional feature, and prerequisite. The 'NEW:' prefix adds slight noise but overall it is well-structured and not bloated.

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 the tool's moderate complexity (four parameters, optional feature, prerequisites), the description covers the main use, timeframes, alternatives, and dependency. An output schema exists, so return-value details are not the description's responsibility. It even provides enough context to distinguish from many portfolio-related siblings, making it highly complete.

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 baseline is 3. The description adds a concrete example of what model_group_id returns (factors like VIX, rates, oil) but does not clarify the 'rollup' parameter beyond the schema's terse 'Attribution period'. Overall the description adds minimal value over the schema descriptions.

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 opens with 'Get historical portfolio analytics' and enumerates specific metrics (Sharpe ratio, volatility, expected return, max drawdown, market beta) benchmarked against SPY. It clearly differentiates from sibling analytics tools by naming compute_returns and test_flow_risk as forward-looking alternatives, and the scope (historical, benchmarked) is precise.

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 ('backward-looking') and names alternatives ('for forward-looking risk, use compute_returns or test_flow_risk'). Also provides a prerequisite ('Requires compute_betas to have been run first via analyze_quantitative'), giving clear context on when this tool is applicable.

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