propose_library_organization

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

No annotations are provided, so the description carries the full burden. It discloses the algorithm ('Uses abstracts and titles to embed papers, then clusters them with k-means'), the auto-detect behavior for n_clusters=0, and the output nature. However, it does not explicitly state whether the tool is read-only or modifies the library, though 'propose' implies non-destructiveness.

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: two short paragraphs and an Args section. It front-loads the purpose and method, then details parameters. Every sentence adds value without redundancy.

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 presence of an output schema (though not shown), the description adequately covers the tool's behavior: algorithm, parameter effects, and return type. It does not mention prerequisites (e.g., library having papers with abstracts) or error conditions, but for a read-only proposal tool, this is acceptable.

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 0%, but the description provides clear semantics for both parameters: n_clusters ('0 = auto-detect (sqrt of library size)') and min_papers ('Minimum papers per cluster to report'). This adds value beyond the schema's title and type fields, including auto-detection logic and default values.

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's verb ('Cluster papers by topic and propose an AI-generated collection structure') and resource ('papers'). It distinguishes from siblings like 'propose_skill_improvement' by specifying the domain of library organization. The output is also described ('Returns a proposed collection structure with suggested names and paper counts').

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 implies usage for organizing papers into topic clusters but does not explicitly state when to use this tool versus alternatives (e.g., other library tools or manual organization). No when-not conditions or alternative tools are mentioned.

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