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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds genuinely new behavioral context: the computation runs across five fixed timeframes, and the tool abstains on the Hölder spectrum because tick-level history is not ingested. That abstention contract is the kind of thing an agent cannot learn from structured fields. Missing only return shape or failure modes.

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?

Three sentences, core computation front-loaded, with the limitation last. Slight waste from the repeated filler 'real' ('Real Rescaled-Range ... at each real timeframe ... real excess kurtosis of the real return series'), which crowds out useful detail.

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 read-only single-parameter analysis tool with no output schema, the description says what is computed, over which timeframes, and what is deliberately not computed. An agent knows enough to call it correctly; the only gap is the exact response structure and how short-history tickers are handled.

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?

There is a single parameter with 100% schema description coverage (ticker with examples), so the schema does the work. The description adds nothing about ticker semantics (e.g. whether unsupported tickers or short histories cause abstention), so the baseline 3 applies rather than higher.

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?

Names the concrete metric (Rescaled-Range Hurst exponent) and the data source (historical bars at 15M/1H/4H/1D/1W), plus excess kurtosis of the return series — specific verb+resource. It does not, however, contrast itself with any sibling (e.g. track_volatility_surface or classify_microstructure_regime), so an agent must infer which analysis tool to pick.

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 negative scope statement ('Does not compute a true Hölder singularity spectrum — abstains rather than fabricating one') usefully bounds expectations, but there is no positive guidance on when to call this versus the many other analysis/scanner siblings, and no prerequisites or cost/rate context.

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