normalize_dilution_potency

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the scaling action but doesn't disclose edge cases (e.g., zero dilution factor), units, or whether the operation is safe read-only or mutating. It also doesn't describe the return value or error behavior.

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 a single, compact sentence with no redundant words. It is front-loaded with the key action. However, it is almost too terse, sacrificing clarity for brevity.

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 simple two-parameter tool and absence of output schema or annotations, the description covers the core purpose but lacks details on the exact calculation, parameter definitions, and output. An agent would need to infer the formula and units, which is risky. The tool appears part of a larger assay analysis suite, but no contextual connection is provided.

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 0%, so the description must compensate. It hints that observed_concentration is the diluted measurement and dilution_factor is the ratio, but it doesn't explicitly name the parameters or provide the formula. This is minimal semantic addition and may leave the agent uncertain about exact units or input formats.

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 ('scales') and states the resource ('observed calculations ... back to original stock concentration'). It distinguishes from sibling tools which focus on curve fitting, parallelism, z-factor, etc. However, 'observed calculations' is somewhat vague and the plural 'dilution ratios' doesn't align perfectly with the singular 'dilution_factor' parameter.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies use for normalization of dilution-related measurements but doesn't state exclusions, prerequisites, or context such as assay types. Sibling tools are not referenced.

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