compute_factor_exposure

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

Annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false) already indicate safe read-only behavior. Description supplements by detailing outputs (alpha, betas, R-squared) and data source (Polygon daily data). No contradictions. Could mention cost or rate-limit implications of Polygon API calls.

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?

Two sentences: first defines core action and data source, second lists outputs and regimes identified. No filler, every word 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?

No output schema, but description enumerates key outputs (alpha, market beta, SMB/HML/momentum betas, R-squared, information ratio, tracking error). Sufficient for a factor decomposition tool; could add p-values or standard errors but not essential.

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 has 0% description coverage. Description mentions 'symbol' and implies 'period' (via 'daily data' and default 1y) and 'benchmark' (default SPY), but does not explain expected formats, the enum values for period, or how benchmark affects calculations. Needs explicit parameter guidance.

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 decomposing a symbol's returns into Fama-French 5-factor + momentum exposures using Polygon daily data, listing specific outputs like alpha and betas. It distinguishes from sibling analytical tools (e.g., compute_correlation_matrix) by specifying the factor model and data source.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies it's for factor exposure analysis but doesn't mention exclusions or contrasting tools among siblings like compute_volatility_surface or detect_market_regime.

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