search_knowledge

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

With no annotations, the description carries the full behavioral burden. It discloses cross-project behavior (no cwd auto-scoping), the semantic nature of the search, and the exclusion of source code/git commits. This gives the agent important expectations about scope and limitations, though it does not mention result format or potential side effects (which are likely none).

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 compact, front-loaded with the primary purpose, and every clause adds value — defining content types, scope, usage, and alternative in three sentences.

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 description covers what the tool searches, what it excludes, cross-project behavior, and when to use it versus the sibling. The only missing piece is the output/return format, but given the tool's simplicity and no output schema, the description is still quite complete.

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 schema has 0% description coverage, so the description must explain the parameters. It only implicitly addresses 'query' through examples ('is there a note about X') and completely omits 'top', leaving its meaning and constraints undocumented. This is a significant gap.

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 'Semantic search over the knowledge layer' and enumerates specific content types (memory notes, ADRs, plans, etc.), explicitly excluding source code/git commits. It also distinguishes from the sibling tool rag_query, making the tool's purpose unambiguous.

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 when-to-use examples ('what did we decide / is there a note about X / did we hit this before') and an explicit alternative ('For source-code or git-commit recall, use rag_query instead'), clearly guiding selection.

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