RevenueScope: revenue-first analytics for your EC site

List available sites

list_sites

Read-only

List the sites this caller can analyze, in two groups. my_sites = the sites connected to the signed-in account (each with its display name + domain, so you can match phrases like "the production site" or "revenuescope.jp" without the user pasting a UUID); empty when the caller is not signed in. demo_sites = ready-made sample sites for trying RevenueScope before connecting your own — each is a fictional site with sample data, not a real customer. When signed in (OAuth), prefer my_sites and, if site_id is omitted, default analytics tools to the is_primary=true site. When NOT signed in, my_sites is empty: use a demo_sites site_id and tell the user the numbers come from a sample site, not their own.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`note`	Yes
`my_sites`	Yes
`demo_sites`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

Beyond the readOnlyHint, the description discloses key behaviors: returns two groups, my_sites is empty when not signed in, demo_sites are fictional sample data, and OAuth context. This adds substantial value over annotations and gives the agent full understanding of the tool's runtime behavior.

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 dense but every sentence carries distinct, useful information: the grouping logic, signed-in vs. signed-out behavior, demo data caveat, and default-site guidance. It is front-loaded with the core purpose and remains appropriately sized for the complexity covered.

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?

Despite having no parameters and a simple schema, the tool's behavior in different auth states is fully explained. The output schema exists so return-value details are not required. The description covers all edge cases and context needed for an agent to use the tool correctly.

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?

The tool has zero parameters, so the input schema is trivially fully covered. The description adds indirect parameter guidance for other tools (defaulting site_id to primary), but for this tool itself, no parameter explanation is needed. Baseline 4 for zero-parameter tools is appropriate.

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 opens with a specific verb+resource ('List the sites this caller can analyze') and immediately distinguishes the tool from analytics siblings by clarifying it returns two groups (my_sites and demo_sites). This clearly separates it from the other tools that analyze specific site metrics.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance: prefer my_sites when signed in, use demo_sites when not signed in, and default to is_primary=true when site_id is omitted. It also instructs to inform users when demo data is used, covering both usage context and alternatives.

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

All RevenueScope: revenue-first analytics for your EC site tools Inspect

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TDQS

A4.6/5.0

Disambiguation5/5

Each tool has a distinct purpose: AI traffic analysis, multi-dimensional breakdown, competitor SEO snapshot, content playbook, keyword performance, page trend, priority insights, summary, site listing, and budget allocation. Overlapping domains like search performance are clearly separated by focus (query-level vs page-level vs competitor).

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., get_ai_traffic, get_breakdown, list_sites). The verbs are uniformly descriptive ('get', 'list', 'suggest'), and the naming style is predictable and clean.

Tool Count5/5

With 10 tools, the server is well-scoped for a comprehensive analytics platform. Each tool covers a critical area (summary, traffic sources, breakdowns, search performance, competitor analysis, content actions, budget allocation) without unnecessary bloat.

Completeness5/5

The tool surface covers all major aspects of revenue-first e-commerce analytics: overall KPIs, AI traffic, channel/page/session breakdowns, search keyword and content performance, competitor insights, trend analysis, priority diagnoses, and budget recommendations. No obvious gaps for the stated purpose.

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