RUNaDIVA

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

With no annotations, the description carries the full burden, and it does disclose the return vocabulary (EXECUTE/SWITCH/VERIFY/BLOCK) plus that evidence and measurable savings come back. That is genuinely useful output semantics. It does not say whether the call is read-only, whether any state is mutated, or what governs the decision thresholds.

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 short sentences, front-loaded with the core action and immediately followed by the return contract. No filler, though 'with transparent evidence and measurable savings when available' is slightly padded relative to the information it carries.

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 4-parameter tool with nested objects, no output schema, and no annotations, the description covers the decision output but omits how the nested option and constraint fields are interpreted and what the currency parameter does. The agent can form the call but not fully predict the result semantics.

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% with four parameters including a nested options array and constraints object. The description only loosely gestures at 'proposed option', 'alternatives', and 'constraints' and never explains currency (a required field), the required option fields (id, total_cost), or how constraints influence the decision.

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 gives a specific verb and resource: evaluate a proposed economic option against caller-supplied alternatives and constraints. It also stakes a clear boundary ('Does not search external markets'), so the agent can tell what class of work this does. It stops short of naming or contrasting with the sibling evaluate_sandbox_case.

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 implies when to use it (you have a proposed option plus caller-supplied alternatives/constraints) and gives one negative condition (no external market search). However, it never routes the agent between this tool and evaluate_sandbox_case, which is the key ambiguity given the sibling set.

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

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

With no annotations provided, the description carries the full behavioral burden and delivers almost nothing. It does not disclose whether evaluation mutates state, has side effects, is deterministic, requires setup, or returns a verdict versus raw data.

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?

It is a single front-loaded sentence with no wasted words, which is structurally fine. But the brevity reflects under-specification rather than efficiency, so it does not earn a high conciseness score.

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 tool with an undocumented enum parameter, zero annotations, and no output schema, the description is too thin. An agent lacks the context needed to pick the right case value or anticipate the result.

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 and does not. The single 'case' parameter's enum values (execute, switch, verify, block) are never explained, leaving the agent no way to know which case it is choosing or what each implies.

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 verb ('evaluate') and resource ('fixed synthetic RUNaDIVA sandbox case'), so the general action is clear. However, 'RUNaDIVA sandbox case' is unexplained jargon and the description does not distinguish this from the sibling evaluate_economic_decision, so an agent cannot confidently route between them.

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?

There is no when-to-use guidance, no preconditions, and no mention of the alternative evaluate_economic_decision despite it being the obvious competing tool. The word 'sandbox' vaguely implies a test context but no explicit selection criteria are given.

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