knowledge_search

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('search') but doesn't describe what 'search' entails—whether it's full-text, keyword-based, returns snippets or full content, has pagination, requires specific permissions, or has rate limits. For a search tool with zero annotation coverage, this leaves critical behavioral traits unspecified.

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 extremely concise at three words, with no wasted language. It's front-loaded with the core action ('search'), making it easy to parse quickly. Every word earns its place by specifying the action and target, though this brevity comes at the cost of 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?

Given the tool's complexity (a search operation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns (e.g., results format), how it behaves (e.g., ranking, filtering), or prerequisites (e.g., workspace access). For a search tool in a knowledge system with many siblings, more context is needed to use it effectively.

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 0%, meaning parameters 'workspace', 'query', and 'limit' have no documentation in the schema. The description doesn't add any parameter semantics—it doesn't explain what 'workspace' refers to (e.g., a workspace ID or name), what 'query' should contain (e.g., search terms), or how 'limit' affects results. This fails to compensate for the schema's lack of descriptions.

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 'Search workspace knowledge' clearly states the verb ('search') and resource ('workspace knowledge'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'knowledge_list' or 'knowledge_read' that might also retrieve knowledge, leaving ambiguity about what makes this specific search operation unique.

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 no guidance on when to use this tool versus alternatives. With siblings like 'knowledge_list' (likely listing knowledge items), 'knowledge_read' (likely reading specific items), and 'knowledge_archive' (likely archiving), there's no indication of when search is preferred over these other retrieval methods, leaving the agent to guess based on tool names alone.

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