save_knowledge

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

No annotations provided, so description carries full burden. It discloses that information will be available in future conversations, explains append behavior (add vs. replace), and mentions return status. Missing details on persistence guarantees or error handling, but generally transparent.

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?

Well-structured with clear sections (purpose, usage, args, returns, examples). Slightly verbose due to bullet list and examples, but each sentence adds value. Front-loaded with purpose and usage.

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?

Given 3 parameters, no annotations, and an output schema (implied), the description covers all needed aspects: purpose, usage context, parameter semantics, examples. No gaps identified.

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 has no parameter descriptions (0% coverage), so description adds significant meaning: explains topic as short descriptive name, content as knowledge with markdown, append as additive or replacement. Includes examples, greatly aiding correct parameter usage.

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 it saves learned information about the Universe database, using specific verb and resource. It distinguishes from sibling tools like list_knowledge, search_knowledge, and delete_knowledge by focusing on persistence.

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?

It provides explicit guidance on when to use (persist discoveries about schema, file structures, etc.) and what to save (good things to save list). However, it does not explicitly mention when not to use or differentiate from alternatives like update operations.

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