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yax_collect_ar_invoices

Analyzes open invoices by aging buckets (30/60/90+ days) and sends escalating follow-up emails to overdue clients. Returns invoice count, overdue amount, and emails sent per bucket.

Instructions

Analyzes open invoices by age (30/60/90+ days) and sends escalating follow-up emails to overdue clients. Returns invoice count, total overdue amount, and emails sent per bucket.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aging_bucketsNoOptional custom aging thresholds in days, e.g. [30, 60, 90]. Defaults to [30, 60, 90].
send_emailsNoIf true, sends follow-up emails to overdue clients. Defaults to true.
escalate_atNoDays overdue at which to escalate to a senior contact or legal notice. Defaults to 90.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNoTrue if AR run succeeded.
run_idNoRun ID for receipt retrieval.
invoices_scannedNoTotal invoices analyzed.
overdue_countNoNumber of overdue invoices.
total_overdue_usdNoTotal USD value of overdue invoices.
bucketsNoInvoice counts per aging bucket: bucket_30, bucket_60, bucket_90_plus.
emails_sentNoNumber of follow-up emails dispatched.
Behavior5/5

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

Annotations provide no behavioral details beyond safety hints. Description fully compensates: reveals it sends escalating emails, lists return values (invoice count, overdue amount, emails sent per bucket). No contradiction with annotations.

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?

Two sentences with no fluff. First sentence front-loads purpose and behavior; second lists outputs. Every word earns its place.

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 full schema coverage, safety annotations, and an output schema, the description is complete. It covers purpose, behavior, and returned data without needing to repeat structured fields.

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?

Schema coverage is 100% with clear parameter descriptions. Description adds no new meaning beyond schema; it references default buckets but doesn't enhance parameter understanding. Baseline 3 applies.

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?

Description uses specific verb+resource: 'Analyzes open invoices by age (30/60/90+ days) and sends escalating follow-up emails to overdue clients.' Clearly states action, target, and behavior, distinguishing it from siblings like yax_forecast_cash_flow or yax_get_receipt.

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

Usage Guidelines3/5

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

No explicit when-to-use or when-not-to-use guidance. The description implies usage for overdue invoice follow-up but doesn't compare to alternatives or state prerequisites (e.g., 'Use when you need to send automated reminders').

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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