Invoice Aging logo

Invoice Aging

Organization
openaccountant
invoice-aging

Track unpaid invoices by age bucket and flag overdue payments.

Overview

Publisheropenaccountant
Repositoryskills
Skill nameinvoice-aging
Stars
106
Forks
18
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by openaccountant on GitHub. Read the source before you install it.

Installation

Install the Invoice Aging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/openaccountant/skills/tree/main/business/invoice-aging
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/openaccountant/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/business/invoice-aging .claude/skills/invoice-aging
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Invoice Aging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Invoice Aging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Invoice Aging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Invoice Aging Report

Overview

Analyze accounts receivable by sorting outstanding invoices into aging buckets: Current (0-30 days), 31-60 days, 61-90 days, and 90+ days. Identifies clients with chronically late payments and calculates total exposure.

Wilson Tools Used

  • transaction_search — find payment transactions matched to known clients or invoice references, identify gaps where expected payments are missing

Workflow

  1. Ask for the list of outstanding invoices (client name, invoice amount, invoice date, due date) or ask the user to describe their invoicing pattern.
  2. Use transaction_search to find all incoming payments from each client over the past 6 months.
  3. Cross-reference received payments against known invoice amounts and dates.
  4. For each unpaid or partially paid invoice, calculate days outstanding from the due date.
  5. Sort into aging buckets:
ACCOUNTS RECEIVABLE AGING — as of [Date]
═══════════════════════════════════════════════════════
Client          Current   31-60    61-90     90+     Total
────────────────────────────────────────────────────────
Acme Corp       $2,500      —        —        —     $2,500
Beta LLC            —    $1,800      —        —     $1,800
Gamma Inc           —       —     $3,200      —     $3,200
Delta Co            —       —        —     $5,000   $5,000
────────────────────────────────────────────────────────
TOTALS          $2,500   $1,800   $3,200   $5,000  $12,500
% of Total       20.0%    14.4%    25.6%    40.0%    100%
═══════════════════════════════════════════════════════
  1. Flag any client with invoices in the 90+ bucket.
  2. Calculate weighted average days outstanding.
  3. Recommend follow-up actions: send reminder (31-60), escalate (61-90), consider collections (90+).

Without Wilson

  1. Export your invoice list from your invoicing tool (QuickBooks: Reports > Customers & Receivables > A/R Aging Summary; FreshBooks: Reports > Accounts Aging; Wave: Reports > Aged Receivables).
  2. If no invoicing tool, create a spreadsheet with columns: Client, Invoice #, Amount, Invoice Date, Due Date, Paid Date, Paid Amount.
  3. Calculate days outstanding: =IF(PaidDate="", TODAY()-DueDate, PaidDate-DueDate).
  4. Assign buckets with: =IF(DaysOutstanding<=0,"Current",IF(DaysOutstanding<=30,"Current",IF(DaysOutstanding<=60,"31-60",IF(DaysOutstanding<=90,"61-90","90+")))).
  5. Pivot table: Rows = Client, Columns = Bucket, Values = Sum of Amount.
  6. For weighted average: =SUMPRODUCT(Amount,DaysOutstanding)/SUM(Amount).

Important Notes

  • Wilson tracks cash transactions, not invoices directly. This skill works best when you can provide a list of issued invoices to cross-reference against bank deposits.
  • Partial payments should be tracked. If an invoice is $5,000 and $3,000 was received, the remaining $2,000 is still outstanding.
  • Consider offering early payment discounts (e.g., 2/10 Net 30) for clients consistently in the 61-90+ buckets.

Frequently asked questions

What does the Invoice Aging AI skill do?

Track unpaid invoices by age bucket and flag overdue payments.

Why use Invoice Aging on TypingMind?

Because you install it once and use it with any model. Invoice Aging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Invoice Aging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/openaccountant/skills/tree/main/business/invoice-aging. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Invoice Aging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Invoice Aging?

As many as you like. As long as a model supports skills, you can use Invoice Aging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Invoice Aging AI skill free?

Yes. It is published on GitHub by openaccountant under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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