get_consensus

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

No annotations are present, so the description carries the burden. It discloses a key limitation: the earnings surprise table only includes operating profit and net income, not sales. It does not mention permissions or side effects, but for a read tool that is acceptable. This adds meaningful context beyond the 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 efficiently structured: first a definition, then usage examples, a scope note, and an args section. Every sentence adds value, and it is not verbose. It is front-loaded with the main purpose.

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 tool's simplicity (one parameter, clear purpose) and that an output schema exists, the description is complete. It covers what the tool does, when to use it, its limitations, and its alternative. No important aspects are left unmentioned.

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 0%, so the description must explain the single parameter. It states the format (6-digit stock code) and provides an example ('005930'), adding meaning beyond the bare schema title 'Code'. This is sufficient for a single-parameter tool.

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?

Description clearly states the tool provides consensus data (analyst ratings, target prices) and earnings surprises relative to consensus. It lists example queries that should trigger this tool, and distinguishes from siblings by explicitly directing sales-related queries to get_financial.

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?

Explicit usage triggers are given (e.g., 'target price', 'consensus', 'earnings surprise'). The description clearly says when NOT to use it (for sales figures) and names the alternative tool (get_financial), providing a clear decision boundary.

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