Search Learnings

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

The annotations already convey readOnlyHint and idempotentHint, so the safety profile is covered. The description adds useful behavioral detail about which fields are matched, but it does not disclose result shape, ordering, or whether matches are partial/exact.

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 short sentences with no wasted words. The purpose is stated immediately, and the matching scope follows naturally, making it easy to scan and apply.

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 simple read-only search tool with all parameters documented in the schema, the description is largely sufficient. The main gap is the lack of return-format information, but for a search tool this is fairly implicit.

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%, providing a baseline of 3. The description adds that query matches title, content, and tags, which is helpful, but it does not add meaning for limit or project_name 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 states a clear verb and resource ('Search session learnings by keyword') and adds the scope of matches ('title, content, and tags'), which tells an agent exactly what the tool operates on. It does not explicitly distinguish this from the sibling memory_search tool, but 'session learnings' gives enough specificity.

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 scope 'session learnings' makes the intended use fairly clear, but the description does not explicitly say when to prefer this over memory_search or when not to use it. The usage context is implied rather than directly stated.

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