gid_semantify

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 two operating modes (heuristic proposals vs. AI analysis) and mentions that dryRun previews without applying. However, it is unclear whether the tool modifies project files when dryRun is false. The description could be more explicit about mutation behavior.

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 two short sentences: the first clearly states the purpose, and the second gives specific usage guidance for a parameter. No wasted words, and the information is front-loaded.

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 4 parameters and no required fields, the description covers the main functionality and the two modes. However, it lacks discussion of prerequisites, error conditions, or how it differs from siblings like gid_analyze. It is mostly complete but could be slightly more detailed.

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 coverage is 100%, providing a baseline of 3. The description adds value by explaining the returnContext parameter's purpose for AI analysis beyond the schema. It also mentions the dryRun default, though that is already in the schema. This added context for a key parameter merits a 4.

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 action: 'Propose semantic upgrades' with specific tasks like 'map files to components, assign layers, detect features'. This verb-resource pair is precise and distinguishes it from siblings like gid_analyze or gid_design which focus on different aspects.

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 clear context for using the returnContext parameter: 'Use returnContext: true for AI semantic analysis (reads docs + code names)'. This guides the agent on when to choose that mode. However, it does not explicitly state when not to use this tool or compare it to alternatives like gid_analyze.

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