rails_lens_extract_concern_candidate

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. Description adds valuable context about analyzing cohesion and providing evidence, which enhances transparency beyond the annotations.

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?

A single concise sentence that front-loads the purpose. No unnecessary words, but could be slightly more structured (e.g., break into steps). Still efficient.

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 that an output schema exists, the description does not need to detail return values. It mentions 'konsho' (evidence) which is helpful. However, it omits prerequisites (e.g., that the model must exist and be a Fat Model). Overall adequate for a read-only analysis tool.

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% (though schema itself has parameter descriptions). The tool description adds no additional meaning beyond what the schema already provides for model_name and min_cluster_size. Does not explain parameter format, constraints, or usage context.

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?

Description clearly states it analyzes Fat Model methods by cohesion and presents Concern extraction candidates with evidence. Uses specific verb-resource pairing and distinguishes from siblings like rails_lens_analyze_concern which deals with existing concerns.

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?

No explicit when-to-use or when-not-to-use guidance. However, from sibling context, it is implied that this tool is for extracting new concern candidates while others analyze existing concerns. Missing explicit alternatives or exclusions.

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