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by io.github.MrViolets

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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses key behaviors: the after-window is clamped to now, per-route pageviews are reported only if routes were recorded, and results may carry notes about truncated or uncovered windows. This goes well beyond the annotations and gives the agent actionable expectations.

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?

Three dense, front-loaded sentences convey purpose, window behavior, conditional details, timing guidance, and result-note handling without waste. Every sentence contributes meaningful operational information.

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?

For a read-only analysis tool with an output schema, the description covers the key semantics: window construction, clamping behavior, conditional per-route output, and how to handle result notes. The schema covers parameter details, so nothing essential is missing for correct invocation.

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

Parameters3/5

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

The input schema already documents all parameters with 100% description coverage, including defaults and provenance of annotation_id. The description adds some context about how window_days relates to before/after windows, but most of this is already present in the schema, so the added value is limited.

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

Purpose4/5

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

The description clearly states that the tool measures before/after impact of a recorded annotation in terms of visitors and pageviews. It is specific about the resource (an annotation) and the operation (comparing before vs after), though it does not explicitly differentiate itself from sibling tools like what_changed or query.

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 contextual guidance: wait a few days after shipping, and relay any notes in the result by qualifying percentages accordingly. It does not explicitly state when to prefer this tool over alternatives, but the intended use case is strongly implied by the annotation-focused language.

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

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct resources or analytic questions: site CRUD, annotation handling, overviews, funnels, journeys, and diagnostic checks are separated. A few tools like get_overview, query, and what_changed could overlap when asking 'what happened', but their descriptions differentiate the intended use well.

Naming Consistency3/5

The CRUD tools follow a clean verb_noun pattern (create_site, delete_site, list_sites, update_site_context), but analysis tools mix bare nouns (funnel, journeys), bare verbs (query), adverb-verb compounds (compare_around), and what_* question phrases (what_broke, what_changed). Naming is readable and snake_case is consistent, but the overall convention is not uniform.

Tool Count5/5

15 tools is within the well-scoped range and each tool earns its place: site management, annotation tracking, traffic overview, discovery, diagnostics, and comparison all have dedicated tools. There is no obvious redundancy or padding.

Completeness4/5

The surface covers the core domain well: sites can be created, listed, deleted, and contextualized; annotations can be recorded and listed; analytics support overview, breakdown, funnel, journey, and anomaly questions. Minor gaps exist such as no update/delete for annotations and no single-site getter separate from list_sites, but agents can work around these.

Resources