auto_search

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

The description discloses that it searches, selects, and composes memories, but does not explicitly state whether it is read-only or if it has side effects. Since no annotations are provided, this lack of explicit side-effect disclosure leaves some ambiguity.

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, with the main purpose stated first, followed by a clear usage note. It is well-structured and free of unnecessary detail.

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 provides the core purpose and usage, but it does not specify the exact output format (beyond being a context string) or details about the multi-resolution levels. Given the tool's role in automatic injection, this is sufficient for basic use but lacks some detail for complex interactions.

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 description only repeats the parameter names and defaults from the schema without providing additional semantics. For example, it doesn't explain the purpose of top_k or token_budget beyond their names, which is insufficient given the schema has no descriptions.

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 automatically retrieves and composes relevant memories, which is a specific verb and resource. It distinguishes from sibling memory_search by mentioning the composition into a context string with token budget and multi-resolution levels, though it could be more explicit about the differentiation.

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 explicitly states when to use: at the beginning of every conversation turn to inject relevant memory context. However, it does not explicitly mention alternatives or when not to use, relying on the automatic nature to imply the distinction.

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