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

Annotations already cover the read-only/idempotent/non-destructive profile, and the description adds genuine value on top: it discloses that no LLM is involved (pure SQL), that results are scoped to memory the caller owns, and that a registered handle + secret are required for auth. This is real behavioral context beyond the annotations.

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?

Four tight sentences, front-loaded with the core purpose and scope; each sentence adds something (SQL nature, ownership/auth, return shape). The leading bracketed "[stores]" tag is the only ambiguous filler.

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?

With no output schema, the description usefully enumerates return contents (topics, entities, action_items, summary) and names the auth prerequisites, so an agent knows what it gets back and what's required. Only the undocumented limit/namespace params 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 coverage is 60% — query, limit, and namespace are documented in the schema, while handle and secret are not. The description compensates by explaining that handle identifies owned memory and secret is an auth credential, but it says nothing about limit or namespace semantics. Baseline 3 is appropriate.

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?

States a specific verb+resource ("Search ... extracted memory facts by topic or entity name") and clarifies scope with "pre-extracted facts" and "pure SQL lookup". However it never distinguishes itself from close siblings like search_memory, memory_recall, or recall_memories, so an agent can't tell which search to pick from the name alone.

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?

Implies usage (search facts by topic/entity, no LLM involved) but gives no explicit when-to-use versus the many sibling memory-retrieval tools. No when-not guidance or exclusions are provided, leaving routing to inference.

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