跳到正文
cccskills
免费在 GitHub 公开

ai-bpo-proposal-generator

Generate AI-powered BPO service proposals for Japanese companies in the US market. Use when creating outsourcing proposals with AI service menus, ROI estimation, implementation roadmaps, and bilingual (JA/EN) proposal documents for 在米日系企業向けAI実装.

中文简介正在准备中。当前显示原文说明。

实测评分 未实测

查看安装方法

包含的文件(12)

  • SKILL.md7.0 KB
  • references/client-intake-template.md9.4 KB
  • references/roi-methodology.md7.8 KB
  • references/service-catalog.md9.4 KB
  • scripts/calculate_roi.py13.2 KB
  • scripts/generate_proposal.py19.7 KB
  • scripts/generate_roadmap.py16.3 KB
  • scripts/select_services.py13.2 KB
  • scripts/tests/conftest.py248 B
  • scripts/tests/test_calculate_roi.py7.0 KB
  • scripts/tests/test_generate_roadmap.py6.5 KB
  • scripts/tests/test_select_services.py5.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

AI-Powered BPO Proposal Generator

Overview

Generate comprehensive BPO (Business Process Outsourcing) service proposals tailored for Japanese companies operating in the US market. This skill creates professional proposals that combine AI-powered service offerings with traditional BPO services, including ROI analysis, implementation roadmaps, and bilingual documentation. The output targets "在米日系企業向けAI実装" market positioning.

When to Use

  • Creating BPO service proposals for Japanese subsidiaries in the US
  • Developing AI-enhanced outsourcing offerings for traditional business processes
  • Estimating ROI for AI implementation in back-office operations
  • Building implementation roadmaps for phased AI adoption
  • Generating bilingual (Japanese/English) proposal documents
  • Positioning AI services for the 在米日系企業 market segment

Prerequisites

  • Python 3.9+
  • No API keys required (calculations are local)
  • Dependencies: pandas, jinja2 (for template rendering)

Workflow

Step 1: Gather Client Requirements

Collect client information using the intake questionnaire:

  1. Company profile (industry, size, US operation scale)
  2. Current pain points (manual processes, error rates, processing volumes)
  3. Budget range and timeline expectations
  4. Language requirements (primary communication language)
  5. Compliance requirements (SOX, J-SOX, data residency)

Reference the client intake template:

cat references/client-intake-template.md

Step 2: Select Applicable Service Modules

Review the AI-BPO service catalog and select relevant modules:

python3 scripts/select_services.py \
  --industry "manufacturing" \
  --pain-points "invoice_processing,expense_reporting" \
  --output proposal_services.json

Service categories include:

  • Finance & Accounting: AP/AR automation, expense management, reconciliation
  • HR & Payroll: Onboarding, time tracking, benefits administration
  • Customer Support: Ticket routing, FAQ automation, sentiment analysis
  • Data Processing: Document digitization, data entry, validation
  • Procurement: Vendor management, PO processing, contract analysis

Step 3: Calculate ROI Estimation

Generate ROI projections based on selected services and client volumes:

python3 scripts/calculate_roi.py \
  --services proposal_services.json \
  --volumes '{"invoices_per_month": 5000, "employees": 200}' \
  --output roi_analysis.json

The ROI calculation includes:

  • Current state cost analysis (FTE, error rates, processing time)
  • Future state projections (automation rates, accuracy improvements)
  • Implementation costs (setup, training, integration)
  • Payback period and 3-year NPV

Step 4: Generate Implementation Roadmap

Create a phased implementation plan:

python3 scripts/generate_roadmap.py \
  --services proposal_services.json \
  --start-date "2025-04-01" \
  --output roadmap.json

Standard phases:

  1. Discovery & Assessment (2-4 weeks): Process mapping, data audit
  2. Pilot Implementation (4-6 weeks): Single process, limited scope
  3. Phased Rollout (8-12 weeks): Expand to additional processes
  4. Optimization (Ongoing): Model tuning, process refinement

Step 5: Generate Proposal Document

Create the final bilingual proposal document:

python3 scripts/generate_proposal.py \
  --client-name "ABC Corporation" \
  --services proposal_services.json \
  --roi roi_analysis.json \
  --roadmap roadmap.json \
  --language "bilingual" \
  --output proposal_ABC_Corporation.md

Output Format

JSON Service Selection

{
  "schema_version": "1.0",
  "generated_at": "2025-04-15T10:30:00Z",
  "client_industry": "manufacturing",
  "selected_services": [
    {
      "service_id": "fin-001",
      "service_name": "Invoice Processing Automation",
      "category": "finance_accounting",
      "ai_components": ["document_extraction", "validation", "approval_routing"],
      "estimated_automation_rate": 0.85,
      "monthly_fee_usd": 5000
    }
  ]
}

JSON ROI Analysis

{
  "schema_version": "1.0",
  "analysis_date": "2025-04-15",
  "current_state": {
    "annual_cost_usd": 250000,
    "fte_equivalent": 3.5,
    "error_rate_pct": 4.2
  },
  "future_state": {
    "annual_cost_usd": 120000,
    "fte_equivalent": 1.0,
    "error_rate_pct": 0.5
  },
  "implementation_cost_usd": 75000,
  "annual_savings_usd": 130000,
  "payback_months": 7,
  "three_year_npv_usd": 285000,
  "roi_percentage": 173
}

Markdown Proposal Structure

# AI-BPO Service Proposal / AI-BPOサービス提案書

## Executive Summary / エグゼクティブサマリー
## Company Understanding / 貴社の理解
## Proposed Solution / ご提案ソリューション
## Service Details / サービス詳細
## ROI Analysis / ROI分析
## Implementation Roadmap / 導入ロードマップ
## Pricing / 価格
## Terms & Conditions / 契約条件
## Next Steps / 次のステップ

Resources

  • scripts/select_services.py -- Service module selection based on industry and pain points
  • scripts/calculate_roi.py -- ROI calculation with NPV, payback period
  • scripts/generate_roadmap.py -- Implementation roadmap generator
  • scripts/generate_proposal.py -- Bilingual proposal document generator
  • references/service-catalog.md -- Complete AI-BPO service catalog with pricing
  • references/client-intake-template.md -- Client requirements questionnaire
  • references/roi-methodology.md -- ROI calculation methodology and benchmarks
<!-- proposal-template-bilingual.md was referenced but never shipped; the template is generated dynamically by generate_proposal.py instead. -->

Key Principles

  1. Bilingual by Default: All client-facing documents include both Japanese and English
  2. Conservative ROI Estimates: Use industry-standard automation rates, not best-case scenarios
  3. Phased Implementation: Recommend pilot-first approach to minimize risk
  4. Compliance-Aware: Consider J-SOX, SOX, and data residency requirements
  5. Cultural Sensitivity: Understand Japanese business practices and decision-making processes

Industry Benchmarks

ProcessTypical Automation RateError ReductionCost Savings
Invoice Processing80-90%85-95%50-70%
Expense Reporting70-85%80-90%40-60%
Employee Onboarding60-75%70-85%35-50%
Customer Ticket Routing85-95%N/A60-75%
Data Entry90-98%95-99%70-85%

Pricing Tiers

TierMonthly VolumeBase Fee (USD)Per-Transaction
Starter< 1,000$3,000$1.50
Growth1,000 - 5,000$8,000$0.80
Enterprise5,000+$15,000$0.40

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Track and update action item status from natural language updates like 'Seanのメールには返信しておいた' or 'Lu対応予定'. Integrates with daily-comms-ops workflow. Use when managing action items across communication channels.

中文简介正在准备中。当前显示原文说明。

takusaotome/claude-skills-library102026年10月23日 更新

AI活用提案の専門コンサルタントスキル。LLM・AIエージェントの活用事例知識を基に、業界別、部門別、シーン別に最適なAI導入提案を行います。システム化、業務改善、効率化を得意とし、具体的な活用事例、期待効果、導入ステップを含む実践的な提案を提供します。Use when proposing AI/LLM adoption strategies for specific industries, departments, or business scenarios.

中文简介正在准备中。当前显示原文说明。

takusaotome/claude-skills-library102026年10月23日 更新

AI(LLM)が生成した日本語テキストの「AI臭」を検出・診断し、人間らしい文章にリライトするスキル。 Use when: 「AIっぽい文章を直して」「人間らしくリライトして」「AI臭を消して」「この文章をもっと自然にして」 「テキストのAI感を減らして」「機械っぽさを取りたい」 "make this sound more human", "remove AI tone", "humanize this text", "detect if this is AI-generated". 6つのAI特有パターン(視覚的マーカー、単調なリズム、マニュアル的構成、非コミット姿勢、抽象語の濫用、 定型メタファー)を正規表現ベースで検出し、0-100のAI臭スコアを算出。3つの人間化技法 (バランスを崩す・客観を崩す・論理を崩す)でリライトを実行する。 Note: 検出スクリプトは日本語テキスト専用。英語テキストの場合はClaude自身がreferences/を参照して分析・リライトする。

中文简介正在准备中。当前显示原文说明。

takusaotome/claude-skills-library102026年10月23日 更新

Generate audit-ready internal control design documents from As-Is business process inventories. Produces control IDs, assertion mappings, procedures, SoD analysis, KPIs, materiality thresholds, and implementation roadmaps. Use when building internal controls for new audit engagements, SOX/J-SOX compliance, or process improvement initiatives.

中文简介正在准备中。当前显示原文说明。

takusaotome/claude-skills-library102026年10月23日 更新

Review audit-related documents (control design documents, bottleneck analyses, requirements definitions, etc.) for quality, scoring them 0-100 with a severity-rated findings list. Use when reviewing audit documents, checking control design quality, or verifying cross-document consistency. Supports documents governed by US GAAP, IFRS, or J-GAAP.

中文简介正在准备中。当前显示原文说明。

takusaotome/claude-skills-library102026年10月23日 更新

AWS CLIの専門家スキル。EC2, S3, IAM, Lambda, RDS, ECS等の主要サービスのCLI操作を支援。IAMポリシー設計、クロスアカウント運用、セキュリティ設定、コスト最適化のベストプラクティスを提供。Use when working with AWS services via CLI, designing IAM policies, managing infrastructure, or automating cloud operations.

中文简介正在准备中。当前显示原文说明。

takusaotome/claude-skills-library102026年10月23日 更新

查看 takusaotome 的全部技能

报告此技能的问题