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Get revenue summary

get_revenue_summary
Read-only

Business revenue from this operator's photobooth sessions across EVERY payment channel — gateway payments, cash vouchers (cash collected at the booth) and discount vouchers — grouped by month or day and by currency, with extra-print revenue and AI-effect purchases reported separately. Use this for any question about income, revenue or omzet. It is also the right tool when wallet earnings look too small: cash and voucher money never reaches the wallet ledger, so for operators who take cash the wallet figure legitimately understates income.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd date, ISO YYYY-MM-DD. Omit for all time.
fromNoStart date, ISO YYYY-MM-DD. Omit for all time.
groupByNoBucket size (default month)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo
fromNo
foundNo
sourceNoWhich ledger the figures came from
totalsNo
bucketsNo
groupByNo
mixedCurrencyNo
reconciliationNo

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly and non-destructive behavior. The description adds valuable context by explaining that cash and voucher money never reaches the wallet ledger, so wallet figures understate income, and that extra-print/AI-effect revenue is reported separately. This goes beyond annotation basics and provides interpretive insight.

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

Conciseness4/5

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

The description is two sentences and every clause carries meaningful information. It is slightly dense but not redundant. A bulleted structure could improve skimmability, but the current format is acceptable and efficient.

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?

With an output schema present and annotations covering safety, the description fully covers the business logic: revenue channels, grouping options, separate reporting, and the wallet discrepancy. It also provides concrete use-case scenarios, making it complete for an agent to select and invoke the tool correctly.

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 schema provides complete descriptions for all three parameters (to, from, groupBy), so the baseline is 3. The description reinforces the grouping by month/day and the date range, but does not add new parameter syntax or format details beyond what the schema already offers.

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 clearly states the tool's function: it returns business revenue from photobooth sessions across all payment channels, grouped by month/day and currency, with extra-print and AI-effect revenue reported separately. This specific verb+resource combination distinctly differentiates it from sibling tools like get_wallet_transactions and get_sessions.

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?

The description explicitly instructs to use this tool for any question about income, revenue, or omzet, and recommends it specifically when wallet earnings look too small. This provides clear when-to-use guidance and effectively contrasts with wallet-related alternatives.

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

A4.6/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: account connection/status, credits, gallery stats, project details, revenue, sessions, wallet transactions, project listing, and docs. Descriptions explicitly differentiate between similar tools such as revenue vs. wallet transactions and sessions vs. gallery stats.

Naming Consistency4/5

Most tools follow a verb_noun pattern (get_*, list_*, connect_*, search_*). connection_status deviates slightly by omitting the 'get' prefix, but the overall pattern is predictable and readable.

Tool Count5/5

10 tools is well-scoped for a photobooth analytics and management assistant. Each tool covers a distinct need, from account connection to revenue reporting, with no redundant or unnecessary tools.

Completeness5/5

The tool surface covers the full lifecycle of typical operator queries: account setup, status, credits, project listing/detail, session counts, revenue across channels, wallet ledger, gallery retention, and documentation search. No obvious dead ends or missing operations for the stated purpose.