search_memory

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

No annotations are provided, so the description carries the full burden and largely meets it: it discloses the return shape (id/content/score/type/source per hit), the error contract for top_k < 1, the project-boost behavior, and that client is audit-only. It omits auth/permission requirements and any latency or rate-limit context, keeping it out of 5 territory.

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?

Content is front-loaded and each clause carries information, but the entire description is duplicated verbatim in Chinese and English, roughly doubling the length for the same payload. That redundancy is a real cost against a tight token budget even if it aids bilingual readability.

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 four-parameter retrieval tool with an output schema present, the description covers the scoping model, error behavior, and audit-only client well enough to call correctly. Since an output schema exists it need not detail return values, though it helpfully does; only query semantics and default top_k are left unaddressed.

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%, so the description must compensate, and it does for most parameters: project's scoping effect, top_k's validation boundary, and client's optional/auto-detected/audit-only nature. The query parameter itself is left unexplained and top_k's default (5) and result-count meaning are not spelled out, so it is strong but not complete.

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 states a specific verb and resource — hybrid retrieval over memories and knowledge — and even names the retrieval mechanism (vector semantics + BM25, normalized fusion), so the agent knows exactly what operation this performs. It does not, however, differentiate itself from siblings like read_memory or ask_kb, so it falls short of a 5.

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?

Usage is implied through conditional scoping rules (with project → project sub-store + global; without project → global only), which tells the agent how the call behaves. But there is no explicit guidance on when to choose this over ask_kb or read_memory, and no exclusions stated.

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