physical_constant

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior. The description adds useful behavioral context beyond annotations: it returns value, unit, standard uncertainty, source metadata, and optional unit conversion. It also notes alias support and gives examples. This enriches the agent's understanding without contradiction.

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 two sentences, front-loaded with the core purpose, and includes concrete examples. Every sentence contributes value, with no redundant or vague 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?

Since an output schema exists, the return values are structurally documented. The description covers the tool's domain, source, alias behavior, and optional unit conversion, which is adequate for a simple lookup. However, the omission of precision semantics is a minor gap given the three-parameter schema.

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 only hints at 'optional compatible unit conversion' (mapping to output_unit) and implicitly covers 'query' via the lookup phrase. The 'precision' parameter is entirely undocumented, and no parameter names or formats are given. This leaves the agent with gaps for two of three parameters.

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 clearly states a specific verb ('Look up') and resource ('SciPy's bundled CODATA table') with a scope ('by common alias or name'). It distinguishes itself from siblings like calculate and convert_units by focusing on physical constant retrieval, and the examples (c, G, hbar) reinforce its domain.

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 implies the primary use case (looking up physical constants) but does not explicitly contrast with sibling tools like convert_units or calculate. It doesn't state when to prefer this over alternatives or mention any exclusions (e.g., 'not for general unit conversion'). The context is clear but lacks explicit guidance.

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