decide_score

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

No annotations are provided, so the description must carry the full behavioral burden. It discloses that the tool returns a ScoreDecision JSON with expected_score and per-tier probability mass, which is useful, but it does not mention side effects (e.g., whether it is read-only), error behavior, determinism, or any constraints on the state object. For a decision tool, this is minimal.

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 concise (two sentences) and front-loads the primary purpose. The second sentence adds needed detail about the tiers format and return type. It is efficient with no filler, though the tier format explanation is a bit dense.

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 four parameters, nested objects, and an output schema that is not provided in the definition, the description is incomplete. It fails to describe the state object, criteria, and allow_abstain, and does not clarify the expected behavior or edge cases. The return format is mentioned but not elaborated. An agent would struggle to call this correctly without additional context.

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 explains the tiers parameter in some detail (list of strings or dicts with label/value and optional score weight), but provides no information about state, criteria, or allow_abstain. These parameters remain underdocumented, leaving the agent to guess their format and purpose.

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 states a clear verb ('Rate') and a specific resource ('state across ordered tiers'), with an example ('severity levels') that grounds the purpose. It does not explicitly name sibling tools to differentiate, but the focus on tiers and the return type (ScoreDecision with probability mass) makes the function distinct within the decision family.

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 no guidance on when to use this tool versus the siblings (decision_status, decide_choice, decide_noul). It only hints at usage via 'ordered tiers,' but does not state prerequisites, exclusions, or alternative selection criteria. An agent has to infer the appropriate context.

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