decide

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It details the return structure (confidence score, supporting evidence, applicable procedures, conflict detection) and explains the effect of the 'fast' parameter (skip LLM synthesis). It does not mention authorization, rate limits, or idempotency, but the overall behavior is sufficiently transparent for an AI agent to understand side effects and outputs.

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 extremely concise, consisting of two sentences plus a usage note. It front-loads the primary purpose and structure, with no extraneous information. Every sentence adds value, making it efficient for an AI agent to parse quickly.

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 the absence of an output schema, the description compensates by explaining the return format (confidence, evidence, procedures, conflict). The 4 parameters are covered by the schema and the description addresses the key 'fast' behavior. The sibling tools list is diverse, and the description effectively differentiates 'decide' from retrieval-focused tools. The description feels complete for an agent to decide when and how to invoke 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 has 100% description coverage, meaning each parameter is already well-documented. The description adds no new semantic details beyond the schema, except for reinforcing the overall purpose. According to guidelines, when schema coverage is high, the baseline is 3, and the description does not substantially add to parameter semantics beyond what the schema already provides.

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 clearly states the tool's purpose: to ask SharedMemory to make a decision or answer a question based on stored knowledge. It uses specific verbs ('ask', 'make a decision', 'answer') and identifies the resource ('SharedMemory'). The examples ('what should we do?', 'how do we handle X?') further clarify the scope, distinguishing it from sibling tools like query (retrieval) or get_memory (specific memory lookup).

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 explicitly advises when to use the tool: 'when you need a definitive answer about 'what should we do?' or 'how do we handle X?''. This provides clear context for appropriate usage. However, it does not mention when not to use it or explicitly point to alternatives among the many sibling tools, which would improve the guidance.

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