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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds genuine behavioral depth: last-touch tie-breaking (latest anchor of the same subscriber wins), the 1–720 hour window bounds, and how conversions are linked to subscribers via /c/ tracker links or subscription clicks. It does not contradict annotations.

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?

Content is front-loaded with the attribution model, but the body is one ~200-word sentence riddled with nested parentheticals and backticks, making it hard to scan. Every clause carries information, yet structure (bullets or separate sentences for window rules vs. return shape) would improve usability.

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 the return-shape burden and does so well: period summary, rates, % change, daily series, per-mailing rows, and cumulative lag curve. The only gap is guidance on choosing this tool over related report tools.

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%, so the baseline is 3, but the description adds real meaning beyond the schema: what the anchor actually changes (click vs show starting the window), that window is last-touch bounded, and what the conversion labels mean (regs/Lead, ftds/Sale, redeps/Upsell), which the schema does not define.

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?

Opens with a specific verb+resource+scope: 'Web-push post-click attribution' with conversions attributed to push clicks or shows. It is clearly distinguishable from siblings like get_push_overview or get_statistics because it names the attribution model rather than generic reporting.

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 makes the attribution semantics clear enough that an agent can infer this is the right tool for push-driven conversion analysis, but it never explicitly states when to use it versus get_push_overview, get_statistics, or get_report, and gives no exclusions or prerequisites.

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