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

The description does add genuine behavioral detail: "notes marking anything that changed how it is measured" and "counts no site allowance" tell the agent about measurement discontinuities and scope. However, the description depicts a pure read/aggregation operation while the annotations declare readOnlyHint=false, a conflict an agent could act on (e.g., treating this as a mutating call). No other behavioral traits (rate limits, permissions, cost) are disclosed.

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 short, front-loaded sentences with almost no waste; the scope statement leads and the comparison note follows. "Counts no site allowance" is terse to the point of being cryptic, which is the only real flaw.

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?

With no output schema, the description carries return-value burden and mostly discharges it by describing a weekly series plus inline measurement notes. It still omits the shape of the series (units, date keys, whether zeros are filled), so an agent cannot fully predict the payload.

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?

There is a single parameter with 100% schema description coverage, and the schema already says the name must match list_technologies exactly. The description adds no format, casing, or lookup guidance beyond that, so the baseline 3 applies.

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 names a specific resource (weekly adoption of one technology) and its scope (whole period, every site in the corpus), which is far more precise than the title alone. It also implicitly distinguishes itself from siblings like list_technologies and technology_sites by stating it is a per-technology time series rather than a catalog or site list.

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?

"Same population as list_technologies, so the two can be compared" gives real context for pairing the tools, but there is no explicit when-to-use/when-not guidance against the closer siblings technology_sites or stack_breakdown. Usage is implied rather than stated.

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