propose_library_organization

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

No annotations exist, so the description carries the full burden. It describes the algorithm (embedding, k-means) and return structure but does not explicitly state it is read-only or non-destructive. The word 'propose' implies no side effects, but it's not definitive.

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 concise, with a clear first sentence stating purpose, followed by method details and parameter explanations. No unnecessary content, though a bit more structure could improve scannability.

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?

Given the tool's moderate complexity and an output schema, the description adequately covers inputs and overall behavior. It lacks prerequisites (e.g., need papers in library) but is otherwise 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?

Both parameters are explained beyond schema types: n_clusters with auto-detect logic and min_papers with default. This adds significant value since schema description coverage is 0%.

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 explicitly states the tool clusters papers by topic and proposes a collection structure, using specific verbs 'cluster' and 'propose' with resource 'papers'. This clearly distinguishes it from sibling tools like search_library or archive_library_item.

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 explains the method (k-means clustering) but does not provide explicit guidance on when to use this tool versus alternatives (e.g., after importing papers). No exclusions or alternatives are mentioned.

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