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

Description adds details beyond annotations: semantic method lazily computes/caches embeddings, may add latency, and returns fewer results until vault is fully embedded. Annotations already indicate read-only, idempotent, non-destructive; no contradictions.

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?

Two sentences with no wasted words. First sentence states core purpose, second explains methods with trade-offs. Front-loaded with key action and resource.

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?

Despite no output schema, the description sufficiently explains what the tool returns (recommendations) and covers key contextual details like caching and latency. For a read-only tool with limited side effects, this is comprehensive.

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 100%, but description adds meaning by explaining default values and behavioral differences between methods. It clarifies that 'path' can be title or alias, and that 'limit' and 'method' have defaults, going beyond the schema's enum and ranges.

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 the tool recommends similar notes that are not directly linked, using verbs 'recommend' and 'surface'. It distinguishes from siblings like get_neighborhood (direct links) and search_notes (query-based) by focusing on implicit connections.

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 explicitly differentiates when to use 'jaccard' (shared tags/neighbors) vs 'semantic' (embedding similarity), and notes trade-offs like latency for semantic. It implies not to use for directly linked notes, though could explicitly mention alternatives like get_neighborhood.

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