weekday_profile

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

No annotations exist, so the description carries the full disclosure burden, and it discloses very little: it does not say what 'per period' means, where periods come from, how the average is computed (mean of daily values? weighted?), what the result looks like, or what happens with missing days. Only the aggregation intent is conveyed.

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 tight sentences with the core operation front-loaded and the use case second; nothing is wasted. It is brief to the point of under-specification rather than verbose.

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 an analytical tool with two undocumented parameters, no annotations, and no output schema, the description leaves key questions open: which periods are used, and what home_only filters. It is not sufficient on its own to call this tool confidently.

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%, so the description must compensate and it does not. It mentions 'a metric' but never enumerates valid metrics, and the home_only boolean parameter is never mentioned at all despite materially changing the data source.

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?

States a specific computation (average of a metric) over a specific dimension (weekday Mon..Sun) and scope (per period), which distinguishes it from hourly_profile and monthly_trends. It stops short of naming a sibling explicitly, so it is clear but not maximally differentiated.

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 second sentence gives a concrete analytic use case (weekend effects, Sat/Sun vs Fri/Sat), which is genuine usage context. However, it never states when to prefer this over hourly_profile or monthly_trends, nor any prerequisites such as periods needing to be set.

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