How To Collect Webpack Stats

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

With no annotations, the description carries the burden of explaining behavior. It makes clear that the tool returns either a self-applied recipe or an action plan for Copilot to execute, which is the core behavioral distinction. It does not explicitly state that the tool itself does not modify anything, but its instructional nature is reasonably evident.

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?

Two sentences, front-loaded with the primary purpose, and every clause earns its place. The choice between manual and automatic is stated immediately and economically.

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?

For a simple instructional tool with no output schema, the description is complete: it states what the tool produces, the two modes, and why it matters (required by bundle attribution tools). No critical information for calling it correctly is missing.

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 the baseline is 3. The description adds useful meaning for the 'method' parameter by defining manual and automatic modes, but it does not add anything about 'scenario' beyond the schema. The description does not need to compensate heavily because the schema already documents both parameters.

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 uses a specific verb ('Explain how to generate') and a concrete resource ('.next/stats.json'), and it explicitly relates the tool to the bundle attribution tool family. It is clearly distinguished from siblings that analyze or load stats rather than explain how to collect them.

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 gives clear context: this tool is the prerequisite for the bundle attribution tools, and it explains the manual versus automatic modes. It does not explicitly state when not to use it or name an alternative tool, but the context is strong enough for most agent routing decisions.

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