reading-payment-statement

reading-payment-statement is a skill for Claude Code from kazukinagata/shinkoku. It costs 49 tokens per session (1,194 once invoked), scanned A, a copy of reading-deduction-cert, MIT.

An image-reading workflow for extracting structured information from Japanese payment statements, which report payments such as fees, compensation, contracts, or prizes.

In plain words
What is it for?
Use it to capture payment amounts, withholding tax, dates, payer details, and related information for tax records.
Why use it?
It reduces manual copying from documents and uses independent readings or visual confirmation to identify disagreements in amounts, dates, and other fields.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the shinkoku plugin — 24 skills shipped together

Good fit Use it to capture payment amounts, withholding tax, dates, payer details, and related information for tax records.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kazukinagata/shinkoku/reading-payment-statement
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add kazukinagata/shinkoku --skill reading-payment-statement
Clone the repo
git clone --depth 1 https://github.com/kazukinagata/shinkoku

Made for: Claude Code.

Or install shinkoku, the plugin that ships this one along with the rest of its 24 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for reading-payment-statement

README.md
[![agentmods](https://agentmods.dev/badge/skills/kazukinagata/shinkoku/reading-payment-statement/github.svg)](https://agentmods.dev/skills/kazukinagata/shinkoku/reading-payment-statement)
Your own site
<a href="https://agentmods.dev/skills/kazukinagata/shinkoku/reading-payment-statement"><img src="https://agentmods.dev/badge/skills/kazukinagata/shinkoku/reading-payment-statement/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for reading-payment-statement

Your own site · 80×15
<a href="https://agentmods.dev/skills/kazukinagata/shinkoku/reading-payment-statement"><img src="https://agentmods.dev/badge/skills/kazukinagata/shinkoku/reading-payment-statement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,194 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 81% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.01194
Opus 5 $0.00024 $0.00597
Sonnet 5 $0.00010 $0.00239
Haiku 4.5 $0.00005 $0.00119

Measured 10d ago against content hash 4d785211b27f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

reading-payment-statement scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

81% identical to reading-deduction-cert — 93 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/reading-payment-statement/SKILL.md · 98 lines

What it actually says

支払調書 画像読み取り

支払調書(報酬、料金、契約金及び賞金の支払調書)の画像を読み取り、構造化データとして返すスキル。

PDF ファイルの場合

ファイルが PDF(.pdf)の場合、画像 OCR の前にテキスト抽出を試みる。

  1. shinkoku pdf extract-text --file-path <path> を実行する
  2. 抽出テキストに必要な情報(支払金額・源泉徴収税額等)が含まれていれば、テキストから構造化データを生成する
  3. テキストが不十分(スキャン PDF 等)の場合は shinkoku pdf to-image --file-path <path> --output-dir <dir> で PNG に変換し、以下の画像読み取りフローに進む

画像読み取り方法

推奨: デュアル検証(並列2コンテキスト)

精度を高めるため、同じ画像を2つの独立したコンテキストで並列に読み取り、結果を照合する。

  1. 2つの独立した読み取りを実行する: サブエージェントが使える環境では、2つのサブエージェントを並列で起動し、それぞれ独立に画像を読み取る。 各サブエージェントには以下の「基本ルール」と「出力フォーマット」をプロンプトとして渡し、画像ファイルパスを指定する。

  2. 結果照合: 両方の読み取り結果から主要フィールド(金額等)を比較する。

  3. 一致の場合: そのまま採用。「2つの独立した読み取りで結果が一致しました」と報告する。

  4. 不一致の場合: ユーザーに元画像パスと両方の結果を提示し、正しい方を選択してもらう:

    • 差異のあるフィールドを明示する
    • A を採用 / B を採用 / 手動入力 の3択を提示する

フォールバック(サブエージェント非対応の場合)

サブエージェントが利用できない環境では、以下の手順で読み取る:

  1. 画像ファイルを直接 Read ツールで読み取る
  2. 以下の「基本ルール」と「出力フォーマット」に従ってデータを抽出する
  3. 抽出結果をユーザーに提示し、必ず目視確認を依頼する

⚠ デュアル検証が利用できないため、必ずユーザーに目視確認を依頼してください。

基本ルール

  • 画像ファイルは Read ツールで読み取る(Claude Vision が自動的に画像を認識する)
  • 金額は必ず int(円単位の整数)で返す。カンマや「円」は除去する
  • 日付は YYYY-MM-DD 形式で返す
  • 和暦は西暦に変換する(令和7年 → 2025、令和6年 → 2024、平成31年 → 2019)
  • 読み取れないフィールドは UNKNOWN(文字列)または 0(金額)とする
  • 複数ファイルを渡された場合は全て順に処理してまとめて返す

出力フォーマット

画像を読み取り、以下の形式で返す:

---PAYMENT_STATEMENT_DATA---
payer_name: 支払者名
category: 区分(報酬/料金/契約金/賞金)
gross_amount: 支払金額(int)
withholding_tax: 源泉徴収税額(int)
---END---

抽出のポイント

  • 「支払金額」欄を最優先で抽出する
  • 「源泉徴収税額」欄を正確に読み取る
  • 支払者の名称を抽出する
  • 区分(報酬、料金、契約金、賞金のいずれか)を確認する
  • 「報酬、料金、契約金及び賞金の支払調書」というタイトルを確認する
  • 支払を受ける者の情報(住所・氏名)も読み取れれば確認用に含める

複数ファイルの処理

複数のファイルパスが指示された場合:

  1. Glob ツールでファイル一覧を取得する(パターンが指示された場合)
  2. 各ファイルを Read ツールで順に読み取る
  3. 全ファイルの結果をまとめて返す(各結果の前にファイル名を記載する)
## file1.jpg
---PAYMENT_STATEMENT_DATA---
...
---END---

## file2.jpg
---PAYMENT_STATEMENT_DATA---
...
---END---
Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 98 lines · 49 tokens per session scan A 4d785211b27f

Subscribe to this mod's changes

reading-payment-statement is a skill published in the GitHub repository kazukinagata/shinkoku (359 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 1,194 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to reading-deduction-cert, differing in 93 lines, and is treated as a copy.

Related

Other skills, from other repositories

add-pdf-report

Internal implementation skill invoked by /add-native for app-generated PDF report workflows using expo-print and, when present, expo-sharing.

microsoft/power-platform-skills · 30 tokens

add-pdf-viewer

Internal implementation skill invoked by /add-native for native PDF control workflows. Handles HTTPS and file URI PDF viewing with @microsoft/power-apps-native-pdf-viewer 0.2.9+.

microsoft/power-platform-skills · 47 tokens

jangbu-import

A data-import workflow for turning bank files, card records, spreadsheets, receipts, tax invoices, and statement PDFs into a standard set of 13 transaction fields. OCR, or optical character recognition, is used to read information from document images and PDFs.

kimlawtech/korean-jangbu-for · 97 tokens

process-my-statements

Process a batch of PDF or CSV bank and credit-card statements end to end: extract every transaction (parallel Haiku subagents), canonicalize the party names, categorize against your locked chart of accounts (parallel Sonnet subagents), detect inter-account transfers, and assemble a reviewed Google Sheets workbook with…

akiotanaka847/qaio-desktop · 109 tokens

log-an-expense

Log a single expense from a forwarded receipt — image, PDF, or email — and produce one categorized expense plus one balanced journal entry. I extract vendor, date, amount, and line items via multimodal read, pick an account code against your locked chart of accounts (anything below 0.90 confidence lands in Suspense…

akiotanaka847/qaio-desktop · 139 tokens

extract-bank-statement

Extract bank PDF/CSV to transactions.json with running-balance proof (pull bank lines with balance proof). Prefer CSV; Maybank Islamic PDF adapter when needed.

cynco-labs/ai-accounting-skills · 37 tokens