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

Annotations already declare read-only, idempotent, non-destructive, open-world behavior, and the description adds meaningful details beyond that: tickers, company names, and topic words are resolved to structured filters, and unmatched queries return an empty list rather than unrelated stories. It also notes that each result carries an id for the fetch tool, which is useful downstream context.

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 front-loaded with the core action and then efficiently covers query resolution, empty-result behavior, result ids, and the sibling alternative. Every sentence contributes actionable information without repetition.

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 a one-parameter search tool with full schema coverage, an output schema, and rich annotations, the description supplies the remaining behavioral context an agent needs: query interpretation, no-match behavior, follow-up fetching, and when to choose the alternative tool.

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 coverage is 100%, so the schema already documents the single query parameter and its 300-character limit. The description adds semantic value by explaining that ticker symbols, company names, and topic words in the query are resolved into structured filters, going beyond the schema's basic type and length constraints.

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 states a specific verb and resource: search AlphAI's AI-enriched financial news with a natural-language query. It also distinguishes this connector-style tool from the sibling alphai_news_search by positioning the latter for precise filtered queries.

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?

It gives explicit usage guidance: use this for natural-language queries, rephrase with a ticker/company/topic if results are empty, and prefer alphai_news_search for precise filtered queries. The alternative and the when-not condition are both named.

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