runtime_evaluate_many

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the useful non-aborting per-entry failure behavior, but doesn't mention that expressions may execute arbitrary code with side effects or how promise results are serialized. This is partial transparency only.

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?

Three concise sentences, each earning its place: the core operation, the motivating use case, and the failure model. The most important behavioral distinction is front-loaded.

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 two-parameter tool with no output schema, the description gives the essential contract: a map of name to result and per-entry failure handling. It could mention evaluation context or value serialization, but those are minor gaps for an agent selecting and invoking the tool.

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?

The input schema already describes both parameters and has 100% coverage. The description's 'named expressions' mirrors the `{ name, expression }` structure but adds no meaningful detail about `await_promise` or expression evaluation semantics. Baseline 3 is appropriate.

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 names a specific operation — evaluate several named expressions — and explicitly promises a name-to-result map. It distinguishes itself from single-expression evaluation tools by emphasizing the batch, single-round-trip behavior.

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?

It gives a clear use case: sample a lot of app state at once instead of paying a round trip per question. It doesn't explicitly name an alternative like console_evaluate or state when not to use it, but the intended context is well defined.

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