rememb_search

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 effectively describes key behavioral traits: 'Safe, read-only operation with no side effects' establishes safety profile, and 'Returns the top_k most relevant results ranked by similarity' explains the ranking behavior. However, it doesn't mention potential limitations like search accuracy, performance characteristics, or error conditions.

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 perfectly concise and well-structured with three focused sentences that each add distinct value: purpose statement, safety/behavioral information, and usage guidance. There's no wasted language, and the most critical information (search functionality) is front-loaded.

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?

For a search tool with 2 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It covers purpose, safety profile, usage guidance, and basic return behavior. However, without an output schema, it could benefit from more detail about the structure of returned results beyond just 'top_k most relevant results.'

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 100%, so the schema already documents both parameters thoroughly. The description adds minimal value beyond the schema by mentioning 'natural language or keywords' for the query parameter and 'top_k most relevant results' for the top_k parameter, but doesn't provide additional semantic context like query format examples or similarity scoring details.

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 with specific verbs ('Search memory entries') and resources ('by content or tags'), and distinguishes it from sibling rememb_read by specifying 'when you need to find specific entries by topic rather than loading all entries.' This provides clear differentiation from alternatives.

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 provides usage guidance by stating 'Use instead of rememb_read when you need to find specific entries by topic rather than loading all entries.' This gives clear when-to-use and when-not-to-use instructions with a named alternative, which is optimal for agent decision-making.

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