Create Knowledge Library

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

Annotations already flag the tool as non-readOnly and non-destructive, and the description adds valuable behavioral detail: text chunking, compression ratio (15-60×), and the promise of '100% data integrity'. It does not contradict the idempotentHint, and it explains the internal processing enough for an agent to predict effects.

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?

Two sentences carry the entire message with no filler: the first states the action and mechanism, the second adds scope and use cases. Every clause contributes, and the core purpose is front-loaded before any supporting 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?

With an output schema present, the description need not explain return values. It covers the action, the compression behavior, the target use cases, and indirectly signals input expectations. There are no prerequisites or side-effect caveats that an agent would need beyond this description and the structured fields.

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 baseline is 3; the description's compression details loosely connect to n_max's role but do not add parameter-level meaning beyond the schema. The schema already documents name format, text minimum length, and n_max range/default, so the description adds no essential parameter semantics.

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 opens with a specific verb and resource ('Creates a new knowledge library') and immediately distinguishes itself from sibling tools by detailing the compression mechanism ('gravitational memory', 'split into chunks', 'compressed 15-60×'). It clearly targets creation rather than querying, deleting, or verifying, making it unmistakable among the sibling list.

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 clear context for when to use the tool: it is 'Perfect for large documents, codebases, or research papers,' which signals the intended input scale. It does not explicitly exclude alternatives or name sibling tools for other operations, so it stops short of a 5, but the use-case framing gives adequate guidance.

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