vts_gen_compile_db

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

With no annotations, the description must disclose all behavioral traits. It explains the default dry-run behavior, the effect of apply=true, the output location (default out-of-tree vs inTree), and VCS-ignore protection. It does not cover error handling or post-apply feedback, but the key behaviors are well documented.

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 moderately concise, front-loading the core purpose and key behavior (dry-run vs apply). While it contains several details, each sentence adds necessary information. It is well-structured and avoids redundancy, though could be slightly tighter without losing clarity.

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 8-parameter complexity and no output schema, the description covers essential aspects like dry-run, location, and VCS protection. However, it omits prerequisites (e.g., UBT installed, Unreal environment) and post-apply outcomes (e.g., success indicators). This leaves some gaps for an AI agent unfamiliar with Unreal build processes.

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 100%, so baseline is 3. The description adds value beyond schema by explaining default locations (~/.vs-token-safer/db/<project>), the dry-run behavior for 'apply', and the VCS-ignore guard for 'inTree'. This provides richer context for parameter decisions.

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 generates compile_commands.json for Unreal projects to enable clangd indexing. It explicitly mentions the method (UBT GenerateClangDatabase) and contrasts with staying in no-DB text mode, making the purpose specific and distinguishable from sibling tools which handle different tasks like symbol search or configuration.

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 guidance on dry-run vs apply modes and notes that apply takes minutes and requires the UE build environment. However, it lacks explicit when-not-to-use guidance or alternatives beyond the implied choice of no-DB mode. It does not reference sibling tools for comparison, relying on implicit differentiation.

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