memory_find_solutions

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

With no annotations, the description carries the burden of behavioral disclosure. It explicitly states the traversal relationships, giving insight into how the tool operates. It doesn't mention read-only nature or return format, but the 'find' verb implies a non-mutating query, and the relationship list adds transparency.

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 a single sentence, front-loaded with the purpose ('Find concepts that solve a problem') and then specifying the relationships. No wasted words; concise and clear.

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 tool has one parameter and no output schema, so the description should ideally specify what is returned (e.g., a list of concept IDs) to be fully complete. It doesn't, leaving a minor gap for agents needing to know the return format. However, the core behavior is covered.

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 already describes 'problem' as 'Problem concept ID to find solutions for', so the description doesn't add parameter-specific meaning beyond reinforcing the tool's purpose. Schema coverage is 100%, so the baseline of 3 is appropriate.

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 finds concepts that solve a problem, with specific relationship types ('resolved_by', 'prevents', 'mitigates', 'enables'). This distinguishes it from siblings like memory_find_related, which is generic relation finding.

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 clear context: use when you need to find solutions by traversing those specific relationships. It doesn't explicitly say when not to use it or mention alternatives, but the relationship types imply a focused use case.

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