QPTR over time

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

With no annotations provided, the description carries the full burden of disclosure. It provides valuable context: Roblox serves only the last 30 days, older data comes from an archive, and days with no data come back empty rather than zero. This explains important behavioral nuances beyond the annotation-free schema.

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 concise sentences front-load the core purpose and then provide necessary caveats. Every clause earns its place; no filler or redundancy.

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?

Although there is no output schema, the description names the returned fields ('daily click-through rate and impressions') and covers edge cases (archive fallback, empty vs zero). For a low-complexity tool with only two parameters, this is sufficiently complete, though it could explicitly state the output format (e.g., array of daily data points) to be fully self-contained.

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 coverage is 100% (both 'game' and 'range' are documented), so the baseline is 3. The description adds meaning beyond the schema by clarifying date-window behavior ('Roblox only serves the last 30 days; anything older comes from the site's own archive') and missing-data semantics ('days it has neither for come back empty rather than as a zero'), which directly helps with the 'range' parameter.

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 what the tool provides: a game's daily click-through rate and impressions over time. It differentiates from thumbnail-level analysis ('rather than how one thumbnail is doing right now'), though it lacks an explicit verb-resource structure ('Returns...') and does not name a specific sibling tool.

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?

It gives an explicit use case: 'to answer whether it is trending up or down' and contrasts it with a different assessment ('how one thumbnail is doing right now'), implying when to prefer this tool. It does not explicitly name alternative tools or provide exclusion conditions, but the guidance is clear.

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