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

Annotations already cover read-only, idempotent, non-destructive behavior, so the bar is lower. The description still adds real context: the output decomposes into the claim tested, the verdict, and explicitly what it cannot prove, plus the item=earnings grouping and the beginner-oriented plain mode.

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?

Purpose is front-loaded and the whole thing is compact. However, the trailing 'Args: entity; item.' duplicates the schema without adding meaning, and the identifier is incomplete (reading_level and response_mode are omitted), making that line low-value.

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?

An output schema exists, so return values need not be explained. The description covers purpose, trigger, exclusion, and the key parameter behaviors; only the cryptic '→ answer' routing and the truncated arg list leave minor gaps.

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. The description restates that item=earnings covers revenue, profit and EPS and that response_mode=plain suits beginners, but this largely mirrors what the schema already documents rather than adding new syntax or 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?

States a specific operation: reading one metric's recent quarters against the investment case, including what it tests, whether it supports or challenges, and what it cannot prove. It also distinguishes itself from the sibling get_thesis via the 'Not for: the full read' exclusion, though the arrow-to-tool mapping is terse.

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 an explicit trigger ('Use when the user asks: what do X's earnings mean for the thesis') and an explicit exclusion ('Not for: the full read'). The exclusion points at the alternative but names it only obliquely as 'answer', leaving some inference.

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