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Bid Document Review (Lite)

AI-powered bid/tender document review. Extracts text from .docx/.doc files, cross-references bid requirements vs responses, and generates a detailed audit re...
AI驱动的投标文件审查,自动从 .docx/.doc 文件提取文本,交叉核对投标需求与响应,生成详细的审计报告。
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概述

Bid Document Review (Lite)

Review bid/tender documents for errors, contradictions, compliance issues, and fraud indicators using AI analysis.

What it does:

  • Extracts text + tables from .docx and .doc bid documents
  • Cross-references procurement requirements vs bid responses
  • Checks pricing consistency, qualification claims, technical parameters
  • Identifies contradictions, missing information, expired certificates
  • Generates a structured audit report with 🔴/🟡/🟢 risk ratings

Ideal for:

  • Bid managers reviewing submissions before deadline
  • Procurement officers auditing received bids
  • Companies reviewing competitor bids (post-award disclosure)
  • Quality assurance on your own tender responses

Quick Start

  1. Place your bid documents in a working directory:
    • Procurement/tender document (the requirements)
    • Bid/response document (what was submitted)
  1. Tell your agent:

```

Review the bid documents in [directory]. The procurement document is [file1]

and the bid response is [file2].

```

  1. The agent will:
    • Extract all text and tables
    • Analyze against the checklist below
    • Generate a structured report

Text Extraction

For .docx files:

python3 {baseDir}/scripts/extract_text.py input.docx output.txt

For .doc (legacy) files:

python3 {baseDir}/scripts/extract_doc_text.py input.doc output.txt

Review Checklist

1. Pricing & Commercial

  • [ ] Total price within maximum limit
  • [ ] Unit prices within per-item limits
  • [ ] Tax rate calculations correct
  • [ ] Amount in words matches figures
  • [ ] No abnormally low pricing (dumping risk)
  • [ ] Payment terms match requirements

2. Mandatory Requirements (★ items)

  • [ ] ALL mandatory/starred parameters responded to
  • [ ] Responses meet or exceed minimums
  • [ ] Supporting evidence provided for each claim
  • [ ] No contradictions between different sections

3. Qualification & Eligibility

  • [ ] Business license valid and matching
  • [ ] Required certifications in-date
  • [ ] Performance track record meets minimum
  • [ ] Credit/reputation checks provided
  • [ ] Authorization letters (if agent/distributor)

4. Technical Response

  • [ ] All technical parameters addressed
  • [ ] Claims supported by test reports/certificates
  • [ ] Product model matches throughout document
  • [ ] Standards referenced are current (not withdrawn)
  • [ ] Delivery timeline realistic vs. claimed

5. Document Integrity

  • [ ] Bidder name consistent throughout
  • [ ] Signatures and seals present where required
  • [ ] Dates logical (no future dates, no pre-bid dates)
  • [ ] Page numbering sequential
  • [ ] No template placeholders left unfilled (e.g. [X], [TBD])

6. Common Red Flags

  • [ ] Identical test results matching nominal values exactly (fabrication indicator)
  • [ ] Contracts with missing signatures or blank fields
  • [ ] Expired certificates/qualifications submitted as valid
  • [ ] Third-party materials without clear authorization
  • [ ] Inconsistent company names across documents

Report Format

Generate the report in Markdown with this structure:

# Bid Review Report

## Project Info
- Procurement: [name]
- Bidder: [name]
- Date: [date]

## Summary
| Category | Status | Notes |
|----------|--------|-------|
| Pricing  | ✅/⚠️/❌ | ... |
| Mandatory params | ✅/⚠️/❌ | ... |
| ...      | ...    | ...   |

## 🔴 Critical Issues (may cause disqualification)
### 1. [Issue title]
- Location: [where in document]
- Detail: [what's wrong]
- Impact: [consequence]
- Recommendation: [fix]

## 🟡 Medium Issues (affects scoring)
...

## ✅ Positive Findings
...

## Checklist Summary
[Completed checklist with pass/fail for each item]

Dependencies

  • Python 3.6+
  • python-docx (pip3 install python-docx)
  • olefile (pip3 install olefile) — for .doc files only

Limitations (Lite Version)

This lite version covers text-based review only. It does not include:

  • Image extraction and visual analysis (certificates, contracts, photos)
  • Automated image fraud detection (watermarks, stock photos, expired seals)
  • PDF report generation
  • Image compression/optimization for API cost savings

For full image review capabilities, see the complete bid-review skill.

Built From Real Experience

This skill was developed from reviewing 3 real bid documents (1,800+ pages, 2,600+ images) in the road maintenance equipment industry. Every checklist item comes from an actual issue found in production reviews.

Issues discovered include: fake test data, stolen web images with visible watermarks, technical parameters contradicting government records by 4 tons, expired certificates submitted as valid, and 30+ pages of copied filler content.

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-30 14:02 安全 安全

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