Snapshot robot hardware into a WaffleForm (experimental beta)

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

All annotations are false, so the description carries the full burden, and it performs well: it discloses auto-detection behavior, the side-effect of writing a WaffleForm, the dependency footprint, and the post-condition of data-source queryability. Could be stronger with failure modes (e.g., what happens if no robot is available, whether the directory is created). Not a contradiction, just an opportunity for more.

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?

Three tightly-scoped sentences: purpose, prerequisite/installation context, and side-effect/composition note. There is zero filler, and the most important information (what it does) is front-loaded. Every sentence adds distinct value.

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 the tool's complexity (1 optional param, no nested objects, output schema present), the description covers the essentials: core behavior, setup prerequisite, and downstream consumption model. Gaps include the role of the `directory` parameter and what happens on failure, but for a tool of this size these are minor. The description respects the line of what structured fields already convey and adds meaningful orchestration context.

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?

With 0% schema description coverage, the burden falls on the description to explain the `directory` parameter, but it's never mentioned. The schema itself only gives a name and default ('.'), so an agent must guess whether it's the output destination, the robot's config directory, or a scan root. Given the description does zero compensation for its single parameter, a 2 is appropriate here.

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-resource pair ('Auto-detect the robot's current hardware, firmware, and software') and clearly states the output ('return the resulting hardware state' and 'writes a WaffleForm'). It clearly distinguishes this from siblings like run_pipeline or query_messages by establishing a unique outcome (queryable data source) and the experimental beta caveat in the title adds useful maturity context.

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?

Discloses a hard prerequisite ('Requires the waffle CLI on PATH (cargo install waffle-iron)') and implies when it's useful by noting the output is 'immediately queryable as a data source.' It stops short of explicitly naming alternatives or excluding contexts (e.g., 'don't use for X, use save_pipeline instead'), so it loses a point here, but the practical when-to-use context is well covered.

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