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

Annotations already cover safety (readOnly, idempotent, non-destructive), yet the description adds materially new behavioral context: no API key required, free, judged by the house AI with calibration pending, and a scope disclaimer (not news, not advice). The pending-calibration caveat is exactly the kind of trust-relevant detail annotations cannot express.

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?

Front-loaded with the verb, resource and rating scale, and every clause carries information (scope, filters, precedence, auth, cost, disclaimer). Slightly over-packed, and the trailing 'venues by code' is opaque rather than clarifying, keeping it off a 5.

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?

With no output schema, the description still tells the agent what comes back: a per-market rating drawn from a four-value scale plus the single deciding measure, and, when market is given, rating history, daily session stats and a 24-hour profile. Auth, cost, filter precedence and provenance are all covered, so nothing needed for a correct call is missing.

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 the baseline is 3, but the description goes further by explaining cross-parameter interaction (the three filters are ignored when market is supplied) and by restating the enum value sets inline (session, rating, reference_type). That interaction rule is real meaning beyond the schema.

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 a specific verb (Read) and a precisely scoped resource: tradability ratings (usable/thin/avoid/insufficient) for every index and ETF perp on the xyz dex, overall and per session. The scope is unambiguous, but no sibling is named or contrasted (guardrail_subindices is the nearest neighbor and is not mentioned), so the agent gets no explicit routing cue.

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?

Gives clear operative guidance on the filtering args and their precedence: session, rating and reference_type filter the list and are ignored when market is given, and market instead returns rating history, daily session stats and a 24-hour profile. It does not state when to prefer this tool over any alternative, but for a read-only data endpoint the context supplied is sufficient.

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