batch_decide

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

Annotations already establish read-only, idempotent, and non-destructive behavior, so the bar is lower. The description adds meaningful behavioral context by stating decisions are 'ordered' and that this is 'API batching, not parallel inference,' which is not captured by annotations.

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 three sentences, front-loads the main purpose, and contains no filler. The either/or context rule is concise and directly actionable.

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?

The description covers the core batching semantics and the key context-mode constraint, and an output schema exists to describe return values. However, for a 5-parameter tool with several enums, it leaves failure_policy and response_detail semantics implicit and does not differentiate from the `decide` sibling.

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?

With 0% schema description coverage, the description must compensate for parameter meaning. It usefully clarifies the shared_context vs. item-context relationship, but it does not explain failure_policy, response_detail, or confidence_threshold beyond their names and enum values.

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 specific action and resource: 'Make ordered bounded decisions in one MCP request.' It clearly conveys batch scope and distinguishes itself from parallel inference, though it does not explicitly contrast with the sibling `decide` tool.

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 an explicit either/or usage rule: supply `shared_context` and omit item contexts, or omit `shared_context` and provide per-item contexts. It does not state when to prefer this over `decide` or `filter`, but the batching context is clear.

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