email_apply_rules

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

Without annotations, the description effectively discloses key behavioral traits: defaults (substring, case-insensitive, first-match-wins), adjustable parameters (match_mode, case_sensitive), action precedence for 'all' mode, and the safety recommendation of dry_run. It does not mention rate limits or auth requirements, but covers the core operational behavior well.

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 a single concise paragraph that front-loads the purpose and then provides defaults, options, and a safety recommendation. Every sentence contributes useful information, though it could be slightly restructured for improved readability (e.g., bullet points for defaults).

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 complexity (7 parameters, rule-based logic) and no output schema, the description covers core functionality and recommendations but omits the return value/response format and details on error handling or the 'search' parameter usage. Some important context is missing for fully autonomous selection.

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 43%. The description adds context beyond the schema by explaining the default matching logic and the effect of match_mode and case_sensitive. However, it does not elaborate on all parameters (e.g., limit, folder, search) beyond what is in the schema, providing only moderate added value.

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 scans a folder and applies rules to move, mark, or delete emails, with specific default behaviors (substring, case-insensitive, first-match-wins). It differentiates from sibling tools like email_mark, email_delete, and email_move_messages by focusing on batch rule application.

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 provides usage guidance by strongly recommending dry_run=true for safety and explains default matching behavior. It does not explicitly state when to use this tool versus alternative sibling tools for individual actions, but the context of rule-based batch operations is implied.

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