search_my_engineering_memory

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

With no annotations provided, the description carries the full burden. It does disclose that the tool searches metadata, READMEs, architecture documentation, and source code, and returns ranked results. However, it does not explain ranking criteria, potential coverage limitations (e.g., archived/private repos), or output structure, though the output schema mitigates the latter.

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 and front-loaded: the first sentence states purpose, the second adds detail on sources and ranking, and the Args block is a clear, structured parameter list. Every sentence earns its place; no fluff or redundancy.

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 search tool with an output schema, the description covers the essential aspects: purpose, scope, data sources, ranking, and all parameters. It lacks explicit usage differentiation (addressed in dimension 2) but is otherwise sufficient for correct invocation and interpretation. The absence of annotations is less critical for a read-only search operation.

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 itself has no descriptions (0% coverage), but the description includes an Args block that clearly explains both parameters: 'keyword: the text to search for' and 'limit: maximum number of ranked results to return.' This fully compensates for the schema's lack, adding meaning beyond the type/default information.

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 a specific action ('Search') and resource ('your engineering memory across all of your repositories'), with the second sentence enumerating what is searched (metadata, READMEs, architecture docs, source code) and noting ranked results. This differentiates it from siblings like search_code (code-only) and search_repository (likely single-repo) by emphasizing cross-repo scope and ranked output.

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 implies usage context: a broad search across all repositories, including documentation and code. However, it provides no explicit guidance on when to use this tool versus sibling tools like search_code or search_repository, and no exclusions or alternative recommendations are mentioned.

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