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

With no annotations, the description carries the full behavioral burden. It discloses output ordering ('highest first'), the data source ('precomputed per-cell-line stats'), and performance ('fast'), which is meaningful. It does not mention error handling or exact return structure, but for a read-only query tool this is acceptable. The behavior is transparent enough for safe invocation.

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 compact and front-loaded with the primary action. The first sentence states the core operation, the second gives example queries, and the third provides an alternative. Every sentence earns its place without redundancy or fluff.

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?

For a simple tool with 2 well-documented parameters and no output schema, the description provides sufficient context: it clarifies what is returned (genes with mutation counts), the ordering, and the data source. It also points to the relevant sibling tool for broader needs. It could mention error cases, but overall it is complete enough for correct selection and invocation.

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 baseline is 3. The description does not add additional parameter detail beyond what the schema already provides (e.g., exact name example and limit range are in the schema). It mentions 'cell line' generically but doesn't clarify the parameters further. Since the schema is thorough, this is adequate.

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 a specific verb+resource: 'Rank the most-mutated genes within one specific cell line.' It clearly states the function and provides example questions ('what is the top mutated gene in <cell line>') that anchor its purpose. It also distinguishes from sibling tool `get_cell_line` by noting it returns only top genes, not the whole profile.

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 gives explicit usage context: it answers specific question types and notes results come from 'precomputed per-cell-line stats (fast)' implying quick lookups. It also provides an explicit alternative: 'For the whole profile of the line use `get_cell_line` instead.' This is a clear when-to-use and when-not-to-use directive.

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