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Compare around a change

compare_around
Read-only

Before/after impact of a recorded annotation: visitors and pageviews in the N days preceding vs following it (window_days, default 7). The after-window is clamped to now. If the annotation recorded routes, the result also reports per-route pageviews before vs after. Wait a few days after shipping. If the result carries a note (truncated after-window, or a before-window not covered by available data), relay it and qualify the percentages as the note directs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
siteNothe site's data-site code, from its script tag or list_sites. Omit when the account has a single site. In a tracked project, read the code from the script tag before asking the user.
window_daysNodays on each side of the annotation (default 7)
annotation_idYesthe annotation to measure around, from record_annotation or list_annotations

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
siteYes
afterYes
beforeYes
changeYes
routesNo
annotationYes
window_daysYes

TDQS

A4.7/5.0
Behavior5/5

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

With readOnlyHint=true already conveying safety, the description adds valuable behavioral details: the after-window is clamped to now, route-level pageviews appear when the annotation recorded routes, and a note may be returned indicating truncated or missing data. It also instructs the agent to relay the note and qualify percentages, which is transparent about response semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, with each sentence earning its place: the core function, the window behavior, the routing detail, the timing caveat, and the note-handling instruction. It is front-loaded with the primary purpose and contains no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists and the annotations cover safety, the description covers everything an agent needs: what is measured, how the window works, special-case behavior, and how to handle caveats in the response. Nothing important is left unstated for correct invocation and interpretation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by explaining window_days as 'N days preceding vs following' and highlighting the after-window clamping behavior. This enriches the agent's understanding of the parameter's practical effect without being redundant with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('compare') and resource ('recorded annotation') with the exact metric ('visitors and pageviews in the N days preceding vs following it'). It clearly distinguishes from sibling tools that address other analytical questions or site management, making it unambiguous what this tool is for.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context for when to use the tool (after an annotation has been recorded) and includes explicit guidance to 'wait a few days after shipping.' It does not name alternative tools or state when not to use it, but the annotation-specific framing makes the usage context strong enough for an agent to select it appropriately.

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

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TDQS

A4/5.0
Disambiguation5/5

Each tool maps to a distinct resource or action: site management, site context, annotations, overviews, dimensional queries, funnels, journeys, and anomaly checks. Overlapping pairs like funnel/journeys are explicitly disambiguated in the descriptions, and what_broke vs what_changed cleanly separate problems from notable movements.

Naming Consistency3/5

Most tools follow a clear verb_noun pattern such as create_site, list_annotations, and update_site_context, but funnel, journeys, portfolio_overview, what_broke, and what_changed break that pattern. The names are still readable and somewhat grouped by intent, but the mixed conventions make it harder to predict a tool's role from its name alone.

Tool Count5/5

At 15 tools this sits at the upper edge of the ideal range, and each tool earns its place: site lifecycle, context, annotation timeline, core analytics, discovery reports, and post-deploy checks are all covered. There is no obvious redundancy or filler.

Completeness4/5

The set covers site management, context editing, annotations, overview/query/funnel/journeys/portfolio analytics, and what_broke/what_changed checks, so most workflows have no dead ends. Minor gaps exist, such as no way to edit or delete a mistaken annotation and no explicit tool for updating data-retention settings, but these are workaroundable rather than blocking.

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