Kronvex

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 explains key behavioral traits: the search is semantic (not keyword-based), returns ranked results with confidence scores, and returns empty results if no memories exceed the similarity threshold. It doesn't mention rate limits, authentication needs, or error conditions, but covers the core operational behavior well.

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 efficiently structured with three focused paragraphs: purpose, usage guidelines, and return behavior. Each sentence adds distinct value - no repetition or wasted words. The information is front-loaded with the core functionality stated first.

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 tool with no annotations and no output schema, the description provides good coverage of what the tool does, when to use it, and what it returns. It explains the confidence scoring mechanism and empty result behavior. It could benefit from mentioning the memory types available or error conditions, but overall provides sufficient context for effective use.

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 fully documents both parameters. The description adds minimal value beyond the schema - it mentions 'semantic similarity' which relates to the query parameter, but doesn't provide additional parameter semantics. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 long-term memory', 'return the most relevant stored memories') and distinguishes it from siblings by mentioning semantic similarity and confidence scoring. It explicitly identifies what makes this tool unique compared to tools like 'forget', 'inject_context', and 'remember'.

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 provides explicit guidance on when to use this tool: 'before starting a task, when the user references something from a past session, or when you need project-specific context.' This gives clear situational triggers and distinguishes it from alternative memory-related tools without being misleading.

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