get_analysis_analysts

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

No annotations are provided, so the description carries the transparency burden. It discloses pagination behavior, asset-type limitations, and the set of returned fields (per-analyst scores, current rating, sentiment, price target, latest announcement date). It does not mention auth, rate limits, or error conditions, but for a read-only list tool this is acceptable.

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?

Two sentences, front-loaded with the core purpose, followed by usage guidance. Every phrase adds information; no redundancy or filler.

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?

The description sufficiently covers purpose, return contents, pagination, and asset-type limitations, and the schema covers parameters comprehensively. However, since there is no output schema, the description could ideally specify the response envelope (e.g., total count) or error behavior, leaving a small gap.

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?

The schema already provides 100% coverage of all six parameters, including descriptions and examples for filters and sort_by. The description's mention of filtering by sentiment and sorting by announcement date adds usage context but little new parameter semantics, so baseline 3 is appropriate.

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 uses the specific verb 'Returns' and identifies the resource as 'analyst-level coverage records for an asset', then enumerates the contained data fields. This clearly distinguishes it from sibling tools like get_analysis_recommendations and get_analysis_upgrades_downgrades.

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 states to 'Use for populating an Analysts table in the Analysis module, filtering by sentiment, or sorting by announcement date,' giving concrete when-to-use guidance. It also warns that ETFs and mutual funds 'may return empty results,' a when-not for asset types. However, it does not name alternative tools.

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