bookshelf_indexers

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

No annotations are provided, so the description carries the burden. It does label each operation with WRITE or DESTRUCTIVE flags, which is valuable behavioral transparency. However, it does not mention whether operations require special permissions, are irreversible, or have side effects beyond the obvious modification/deletion. Given the explicit write/destructive flags, it provides a baseline disclosure but not comprehensive behavioral context.

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 compact and front-loaded with the usage pattern, followed by a bullet list of operations. Each operation is described in a single line with a brief purpose and flags. There is minimal redundancy, and the structure is scannable. It loses a point because the list format repeats the tool name prefix (bookshelf_) in every entry, which adds noise, but overall it is appropriately sized for the number of operations.

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 11 operations, which is complex. The description provides an overview and per-operation purpose, but lacks detailed parameter semantics (especially the body format) and does not describe the output schema or return values, despite having an output schema. Given the absence of annotations and the 0% schema coverage, the description is incomplete for operations like update, bulk_delete, and schema fetch, where an agent needs more context to construct correct arguments.

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?

The schema description coverage is 0%, meaning the description does not explain the parameters in detail. The description lists function signatures (e.g., 'bookshelf_create_indexer(force_save=False, body={})') and mentions query params (forceSave) in some cases, which adds some value. However, it does not explain the structure of the `body` parameter or the `arguments` dict for each operation. Since the schema only has `operation` and `arguments` (an open dict), and the description provides only surface-level parameter names, it fails to compensate for the low schema coverage.

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 it operates on Bookshelf indexers with a dispatch pattern, listing each operation with a brief purpose ('Create indexer action', 'Delete indexer', etc.). While it doesn't deeply differentiate each operation beyond the one-liner, the list is sufficient for an agent to map operation names to actions and distinguish them from sibling tools focused on other domains (media library, queue, etc.).

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 general usage pattern: 'Pass operation and an arguments dict matching that operation's parameters.' This is clear. However, it does not explicitly state when to use this tool versus sibling tools like bookshelf_media_library or bookshelf_queue, nor does it provide guidance on selecting among the operations within the tool (e.g., when to use create vs update vs bulk operations). The usage guidance is implicit: use this for indexer-related operations.

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