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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so thoroughly: it reveals that this is a metric-based after-the-fact measurement, explains the Wilson-CI thresholds, clarifies the fade view, and explicitly warns that past accuracy does not imply future results. This is strong transparency beyond the bare schema.

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 information-dense but well organized: a one-line thesis, a compact metric summary, a bulleted view breakdown, and a horizon note. Every sentence serves a purpose, and the critical scoping/interpretation guidance is front-loaded.

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 presence of an output schema, the description does not need to explain return values. It covers all important behavioral aspects, defines the custom views, clarifies the canonical horizon, and provides appropriate caveats. Only the trivial `limit` parameter is under-specified, and that does not meaningfully hurt 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 description coverage is 0%, so the description must compensate for the schema's silence. It adds rich semantics for `view` and `horizon`, including allowed values and their meanings, but `limit` is never described. Since two of three parameters are well covered and the remaining one is a simple optional integer, this is strong but not perfect.

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 identifies a specific resource — the daily honest-track-record leaderboard — with a concrete verb ('Reads') and defines what it measures (21d hit-rate, Wilson CI, vs SPY). It is unambiguous about the tool's function, but it does not explicitly differentiate from siblings like analyst_track_record or analyst_views, so it stops short of a full 5.

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 excellent selection context for the view and horizon parameters, explaining what 'proven', 'fade', and 'cross_regime' mean and interpreting them correctly (e.g., fade is a contrarian signal, not a buy list). However, it does not state when to use this tool versus sibling analyst tools, so the guidance is clear but lacks explicit alternatives/exclusions.

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