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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns user posts with sentiment tags, timestamps, like counts, which is useful context. However, no mention of rate limits, auth needs, or edge cases beyond what annotations imply.

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?

Description is front-loaded with natural language queries, but has some repetition and could be more concise. Still, it communicates the tool's value efficiently.

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 5 parameters, no output schema, and annotations present, the description covers the return data but lacks parameter details. It is adequate but not comprehensive.

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%. Description implies 'symbol' (ticker) and 'filter' (bullish/bearish) through examples, but 'max', 'limit', 'since' are not explained. Only one of five parameters is clarified, leaving significant gaps.

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 states the tool returns StockTwits messages mentioning a ticker, with sentiment tags, timestamps, like counts. It is distinctive from siblings like 'trending_messages' or 'symbol_search', but does not explicitly differentiate.

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?

Provides natural language example queries and explicit guidance: 'Use for retail-investor sentiment, social-volume tracking, contrarian signal.' No when-not or alternatives mentioned, but usage context is clear.

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