bookmind.categorize

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

With no annotations provided, the description carries the full burden. It discloses that the tool uses learned rules, keyword dictionary, and optionally LLM, and that results are staged in 'pending' status. This explains the non-destructive workflow and return of suggestions. However, it does not mention error handling or behavior when LLM is unavailable.

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 three sentences, each providing distinct value: core action, follow-up instruction, and workflow explanation. It is efficient with no filler or repetition.

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 no output schema and no annotations, the description covers the core action and workflow but lacks detail on return format and parameter semantics. It does not describe the structure of the return suggestions or the behavior of auto_apply and confidence_threshold.

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%, so the description must compensate. It does not explain the three parameters (auto_apply, transactions, confidence_threshold). The word 'confidence' appears only in 'confidence-scored suggestions', but no details on the threshold or auto_apply behavior. The description adds no meaning beyond parameter names.

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 auto-categorizes uncategorized QuickBooks transactions using multiple methods (regex, keyword dict, LLM). It specifies that it returns confidence-scored suggestions and stages them in 'pending' status. This distinguishes it from sibling tools like bookmind.approve_categorizations and bookmind.fetch_transactions.

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 directs users to use bookmind.approve_categorizations to apply suggestions and mentions the approval workflow. It provides clear context for when to use this tool, but does not explicitly state when not to use it or compare to alternatives like bookmind.learn_rules.

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