get_similar_notes

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

With no annotations, the description carries the transparency burden. It does disclose the retrieval method (embeddings) and the output categories, which implies a read-only operation. However, it does not mention behavior for missing notes, embedding availability, or the exact meaning of 'available blocks.'

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 one concise, front-loaded sentence that communicates purpose and return value without wasted words.

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?

The tool has no output schema or annotations, so the description must compensate. It lists return types but leaves 'available blocks' ambiguous and provides no failure semantics, output structure, or usage guidance relative to sibling tools. This is adequate but incomplete.

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%, so the baseline is 3. The description adds no parameter-specific detail beyond the schema's existing documentation of note_path, limit, and threshold, and it does not clarify how limit and threshold interact.

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 finds semantically similar notes using embeddings and names the returned data (paths, similarity scores, available blocks). It distinguishes from keyword-based search_notes, but does not differentiate from sibling get_embedding_neighbors, which may also use embeddings.

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?

No explicit when-to-use or when-not-to-use guidance is provided. The phrase 'using embeddings' implies semantic similarity use cases, but there is no comparison to alternative tools like search_notes or get_embedding_neighbors, leaving selection ambiguous.

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