Recall matching memories

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

Annotations already cover read-only, idempotent, closed-world, non-destructive, so the safety bar is met elsewhere. The description still adds genuine value by disclosing that ranking is lexical by default and becomes semantic when a model is configured, which explains why identical queries may order results differently across deployments.

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?

Three short sentences, zero waste, with the core purpose front-loaded before the sibling routing and the behavioral note. Nothing is repeated from the title or schema.

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?

Rich annotations, a full-coverage schema and an output schema mean the description need not explain return values. It covers purpose, routing and ranking behavior, but the mismatch between 'use `search` for metadata filters' and this tool's own `tags`/`min_score` params leaves a small ambiguity an agent must resolve.

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 100%, so `k`, `tags`, `query` and `min_score` are already fully documented with bounds and defaults. The description adds no per-parameter meaning beyond a general mention of ranking, so the baseline 3 applies.

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 and resource ('retrieve full memories') plus the ranking model ('ranked for a natural-language question'), which precisely distinguishes it from `search`. An agent can tell the two apart without opening either schema.

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?

Explicitly routes the agent: 'use this for ordinary recall; use `search` when you need metadata filters, ranking controls or score details.' However, the boundary is muddied because this tool's own schema exposes `tags` (a metadata filter) and `min_score` (a ranking control), so the stated exclusion is not fully consistent with what it accepts.

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