RevenueScope: Japanese EC RPS Benchmarks
Server Details
Ask AI for verified Japan EC RPS benchmarks (5 industries, growing). For non-analytics users.
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- Healthy
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Tool Definition Quality
Average 4.6/5 across 7 of 7 tools scored.
Each tool targets a distinct analytic or management function: summary, channel breakdown, keyword breakdown, budget allocation, demo/list/select sites. No two tools overlap in purpose.
All tools follow a consistent snake_case verb_noun pattern: get_*, list_*, select_*, suggest_*. No mixing of styles or ambiguous verbs.
7 tools is well-scoped for a benchmarking analytics server, covering overview, breakdowns, budget suggestion, and site management without being excessive or insufficient.
The tool surface covers the full user journey: site selection, summary, channel/keyword breakdown, budget allocation, and site listing. No obvious gaps for the stated purpose.
Available Tools
7 toolsget_channel_breakdownAInspect
Return per-channel sessions/revenue/RPS for the given period, plus spend/ROAS/saturation when ad spend is connected (Path B). site_id is OPTIONAL when the request is OAuth-authenticated. Default period is the last 30 days; pass period='today' / '7d' / '90d' or a raw day count (1-365) to override. LLMs should call this after get_site_summary to populate the channel table. Channels without ad spend (organic_search, direct, …) keep the spend-side fields null.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | 30d | |
| site_id | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description discloses default period, period override options, site_id optionality under OAuth, and that channels without ad spend have null spend-side fields. Implies read-only operation without contradiction.
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?
Three sentences, front-loaded with main action. Every sentence provides essential information. No redundancy or fluff.
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?
No output schema, but description lists return values (sessions, revenue, RPS, spend, ROAS, saturation). Covers key aspects adequately. Slight gap: no mention of pagination or error conditions.
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 0%, so description carries full burden. It explains period defaults and allowed formats ('today', '7d', '30d', '90d', integer 1-365), and site_id optionality under OAuth. Adds significant value beyond schema.
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?
Description explicitly states it returns per-channel sessions/revenue/RPS and optionally spend/ROAS/saturation. Verb 'Return' and resource 'channel breakdown' are clear. Distinguishes from siblings like get_site_summary and get_keyword_breakdown.
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?
Explicitly says 'call this after get_site_summary to populate the channel table'. Also notes site_id optionality under OAuth. No explicit when-not-to-use, but sibling differentiation provides context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_keyword_breakdownAInspect
Return per-search-query metrics from Google Search Console (clicks/impressions/CTR/avg position/top landing page) plus an estimated revenue per query for the given period. site_id is OPTIONAL when the request is OAuth-authenticated. Default period is the last 30 days; pass period='today'/'7d'/'90d' or a raw day count (1-365). limit caps the number of queries (default 100). Revenue (est.) = 検索 organic RPS × clicks; it is a conservative estimate (search intent typically converts above the site average) and is 0 until the site has 検索 organic revenue. Keyword ranking is by clicks. Call this to populate a keyword (acquisition-dimension) table alongside get_channel_breakdown.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| period | No | 30d | |
| site_id | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description explains the output, revenue estimation method, and that revenue is 0 until organic revenue exists. Does not mention auth details beyond optional site_id nor potential side effects.
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?
Single paragraph with front-loaded summary, then details. No superfluous sentences; could be slightly more structured but efficient.
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?
Given no output schema, description covers return metrics, revenue calculation, and usage companion. Lacks ordering info and error behavior, but overall adequate for a low-complexity tool.
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?
Despite 0% schema coverage, description adds meaning for all three parameters: period allowed values/default, limit default, and site_id optionality. Could reference min/max constraints from schema.
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 it returns per-search-query metrics from Google Search Console including estimated revenue, and explicitly mentions it populates a keyword table alongside a 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?
Provides explicit call context ('populate a keyword table') and notes optional site_id for OAuth, default period, and limit. Lacks explicit exclusion criteria but is still clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_site_summaryAInspect
Return sessions/revenue/RPS for the given period plus the Path A/B recommendation. site_id is OPTIONAL when the request is OAuth-authenticated — the server falls back to the user's primary site. Default period is the last 30 days; pass period='today' / '7d' / '90d' or a raw day count (1-365) to override. Call this first when a user asks 'how is my site doing?' — it tells the LLM whether ad spend data is available (Path B) or not (Path A).
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | 30d | |
| site_id | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description discloses key behaviors: site_id optionality with OAuth fallback, period defaults and valid formats. It implies a read operation but does not explicitly state it's non-destructive.
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?
Three sentences; first sentence states core purpose, second covers parameters, third gives usage advice. Every sentence earns its place with no waste.
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?
Covers parameters and return value intent well for a 2-parameter tool without output schema. Minor gap: lacks mention of response format or error conditions, but overall complete for the complexity.
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?
Despite 0% schema coverage, the description adds significant meaning: explains period values (today, 7d, 30d, 90d, integer 1-365) and site_id optionality with fallback, far exceeding schema-only info.
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 states the tool returns sessions, revenue, RPS, and Path A/B recommendation for a given period, clearly distinguishing it from siblings like get_channel_breakdown or suggest_budget_allocation.
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?
Explicitly says 'Call this first when a user asks "how is my site doing?"' and explains the decision logic (Path A vs Path B), providing strong guidance on when to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_demo_sitesAInspect
Return the operator-curated public demo site_id(s) for this MCP server. Call this FIRST when a user asks an analytics question without supplying a site_id — use the returned site_id as input to the other tools and mention in your reply which demo site you analyzed.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states the tool is a read operation (returns data) and implies it is safe and public. It does not mention potential errors or authentication requirements, but it is sufficiently transparent for a simple listing tool.
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?
One sentence with two clauses plus a follow-up instruction. Every sentence is essential and front-loaded. No wasted words.
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?
Given no parameters, no output schema, and no annotations, the description covers all necessary aspects: purpose, usage context, and what to do with the result. It is complete for the tool's simplicity.
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?
The input schema has zero parameters, so baseline is 4. No parameter documentation needed.
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 the tool returns operator-curated public demo site IDs. It distinguishes itself from siblings like list_my_sites by specifying 'public demo' and provides context that it is the first tool to call when no site_id is supplied.
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?
Explicitly instructs when to use: 'Call this FIRST when a user asks an analytics question without supplying a site_id'. Also guides to use the returned site_id as input to other tools and to mention the analyzed demo site in the reply.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_my_sitesAInspect
Return the sites owned by the currently authenticated user, with their display name and domain so the assistant can match user references like "the production site" or "revenuescope.jp" without making the user copy a UUID. Requires an OAuth-authenticated request (Claude.ai Custom Integration provides this). For unauthenticated callers, use list_demo_sites instead. The site flagged is_primary=true is what get_site_summary / get_channel_breakdown / suggest_budget_allocation default to when site_id is omitted.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses authentication needs, output fields, and the is_primary flag behavior relevant to other tools.
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?
Three compact sentences with clear, front-loaded purpose. Every sentence provides necessary information without 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?
Given no parameters or output schema, the description fully covers authentication, alternative tool, and default behavior implications.
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?
No parameters exist; description adds value by explaining output (display name, domain) and usage context, exceeding the baseline.
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 explicitly states it returns sites owned by the authenticated user with display name and domain, distinguishing it from list_demo_sites and get_site_summary.
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 specifies authentication requirement and directs unauthenticated callers to list_demo_sites, and explains how the output is used for user references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
select_siteAInspect
Set which of your sites is primary — the one analytics tools default to when site_id is omitted. Use this when list_my_sites returns multiple sites and you want a different default. Requires OAuth authentication; for unauthenticated demo callers, this is a no-op (use list_demo_sites instead).
| Name | Required | Description | Default |
|---|---|---|---|
| site_id | Yes | UUID of the site to mark as primary. Must be one returned by list_my_sites. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It discloses OAuth requirement, no-op for demo callers, and mentions an alternative. However, it does not specify the return value or potential side effects of setting the primary site. Still, it provides substantial behavioral context.
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 sentences: first clearly states purpose, second provides usage conditions and alternatives. No wasted words. Front-loaded with the core function.
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?
For a simple tool with 1 parameter and no output schema, the description covers purpose, usage scenarios, parameter constraint, and authentication. It lacks information on the return value or error handling, but is sufficient for correct agent invocation.
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?
The input schema covers 100% of the parameter with a description for site_id. The tool description adds critical context: 'Must be one returned by list_my_sites,' which goes beyond the schema's UUID format and ensures correct usage.
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 the tool's purpose: 'Set which of your sites is primary — the one analytics tools default to when site_id is omitted.' It uses a specific verb ('Set') and resource ('primary site'), and distinguishes from siblings like list_my_sites and get_site_summary.
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?
Explicitly tells when to use: 'Use this when list_my_sites returns multiple sites and you want a different default.' Also provides conditions and alternatives: 'Requires OAuth authentication; for unauthenticated demo callers, this is a no-op (use list_demo_sites instead).' This is excellent guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
suggest_budget_allocationAInspect
Return a proposed monthly budget split across paid channels (meta/google/tiktok). site_id is OPTIONAL when the request is OAuth-authenticated. Path B (ad spend connected): precise weight = ROAS × (1 − saturation) with expected ROAS uplift. Path A (no ad spend): RPS-weighted proportional split with explicit ±20-30% caveats and a connect_incentive_message. Default period for the underlying ROAS/RPS data is 30 days; pass period='today' / '7d' / '90d' or a raw day count (1-365) to override. LLMs should pass assumptions, limitations, and connect_incentive_message through verbatim — they are hardcoded honest axis.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | 30d | |
| site_id | No | ||
| monthly_budget_jpy | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully discloses behavioral traits: two computation paths, formulas, default period and override options, caveats, and verbatim passing of certain fields. This provides a clear model of what the tool does.
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?
The description is concise and front-loaded with the main purpose. Each sentence adds value, though the inclusion of parameters not in schema slightly clutters the message.
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?
The description explains behavior well but lacks specification of the return format. It also introduces fields not in the input schema, causing a completeness gap. Given no output schema, the description should cover the output shape.
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?
The description adds meaning to 'period' (default and options) and 'site_id' (optional under OAuth), but does not explain 'monthly_budget_jpy' beyond its name. It also mentions parameters 'assumptions', 'limitations', and 'connect_incentive_message' that are not in the input schema, which may confuse an agent.
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 the tool returns a proposed monthly budget split across specified paid channels (meta/google/tiktok). It distinguishes from sibling tools like get_channel_breakdown and get_site_summary, which serve different purposes.
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 provides context on when to use the tool, including two paths based on ad spend connection and optionality of site_id with OAuth authentication. However, it does not explicitly compare to alternatives or state when not to use.
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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