decode_uai_result

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 states the key trait that it never mutates canonical state, which is important. However, it does not describe error handling, what happens on validation failure, or any other side effects. The disclosure is moderate, not exhaustive.

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 concise sentences: 'Validate and expand a compact UAI/1R worker result. This never mutates canonical state.' It front-loads the core purpose and adds a critical behavioral guarantee with zero filler. Perfectly structured for quick parsing.

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 main purpose and non-mutation, and an output schema exists to handle return values. However, it omits details about validation semantics and the specific role of expected_context_hash, leaving some gaps in completeness for a 2-parameter tool. It is adequate but not exhaustive.

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 implies that result_json is the compact worker result and mentions validation, which likely involves expected_context_hash. However, it does not explicitly define either parameter, leaving some ambiguity. It adds partial meaning but not enough to fully offset the 0% coverage.

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 verb ('validate and expand') and resource ('compact UAI/1R worker result'), and clarifies it never mutates canonical state. This clearly distinguishes it from mutation-heavy siblings like compile_uai_context or render_uai_result, making the tool's purpose unambiguous.

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 a clear context: it is used for validating and expanding a compact UAI/1R worker result. It does not explicitly mention alternatives or exclusions, but the context is specific enough that an agent can infer when to use this tool. It lacks explicit 'when-not-to-use' guidance, so it stops short of a 5.

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