detect_regime_hmm

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

Description adds useful behavior beyond annotations: uses hmmlearn with fallback, returns multiple metrics (probabilities, days, transitions, vol regime, Sharpe). Annotations already indicate read-only, idempotent, non-destructive; description confirms and expands.

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 sentence states purpose and outputs, second provides implementation detail and data source. Each sentence adds value; no redundancy.

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?

Description covers purpose, method, data source, and output types. No output schema exists, but description partially compensates by listing return metrics. Could mention output format or structure for completeness.

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 descriptions cover both parameters (symbol, lookback_days) adequately. Description does not add new parameter-specific details beyond schema, but schema coverage is reported as 50% likely due to metric calculation; baseline 3 is appropriate.

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 action ('detect'), resource ('market regime'), method ('HMM on real daily returns'), and lists possible regime outcomes (bull_trending, bear_trending, etc.). Distinguishes from sibling tools like 'detect_market_regime' by specifying HMM and fallback.

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 vs alternatives. Mentions 'Real Polygon data only' but does not elaborate on prerequisites or compare to sibling regime detectors.

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