An intelligent bid and proposal management system that parses multi-format announcements, vectorizes content for semantic search, and automates Notion project creation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install bid-proposal-manager
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install bid-proposal-manager using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Bid Proposal Manager?
The Bid Proposal Manager is a comprehensive technical solution designed to handle the entire lifecycle of bid and research proposal management. By integrating with Openclaw Skills, this agent automates the tedious task of reading through complex PDF, HWP, or DOCX announcements to extract critical data such as deadlines, budget constraints, and eligibility requirements.
At its core, the skill utilizes a PostgreSQL database with the pgvector extension to enable semantic search and RAG (Retrieval-Augmented Generation) capabilities. This allows organizations to maintain a searchable knowledge base of past and present opportunities, ensuring that no requirement is overlooked and that previous institutional knowledge is leveraged for every new submission.
Bid Proposal Manager Use Cases
- Automatically extracting project names, budgets, and submission deadlines from government or private sector RFP announcements.
- Verifying that prepared proposal documents meet all specific formatting and requirement checklists extracted from the announcement.
- Synchronizing complex bid schedules and task lists into organized Notion project databases for team collaboration.
- Searching through a library of past proposals to find similar projects and relevant context using vector embeddings.
How Bid Proposal Manager Works
- The user provides a document file or a web URL containing the bid announcement.
- The document parser identifies the format and extracts structured text and section data.
- The proposal analyzer identifies core fields including project metadata, schedules, requirements, and evaluation criteria.
- Extracted text is transformed into vector embeddings and stored in PostgreSQL via pgvector for future semantic retrieval.
- The system performs a verification check on user-prepared documents to ensure compliance with the original RFP requirements.
- A structured Notion page is automatically generated, populated with tables, checklists, and metadata derived from the analysis.
Bid Proposal Manager Setup
To get started with this skill from the Openclaw Skills collection, ensure you have Python 3 and PostgreSQL 15+ installed.
# Install required parsing libraries
pip install pdfplumber pyhwp python-docx beautifulsoup4 pgvector
# Install pgvector on your system (macOS example)
brew install pgvector
# Initialize the vector database
python3 scripts/vectorizer.py init-db --db-url "postgresql://user:pass@localhost:5432/biddb"
# Export necessary environment variables
export NOTION_API_KEY=your_notion_token
export DATABASE_URL="postgresql://user:pass@localhost:5432/biddb"
Bid Proposal Manager Data Schema & Taxonomy
The Bid Proposal Manager organizes data across three primary layers to ensure maximum searchability and utility:
| Layer | Description |
|---|---|
| Vector Store | PostgreSQL + pgvector storing embeddings for project summaries, eligibility text, and scoring rubrics. |
| Extracted Metadata | Structured JSON containing fields like bid_id, total_budget, submission_deadline, and point_distribution. |
| Notion Integration | A hierarchical database structure where each project includes sub-pages for Table of Contents, Checklists, and original source links. |
Bid Proposal Manager Advanced Features
- Support for multiple embedding providers including OpenAI (text-embedding-3-small), Ollama, and local Sentence Transformers.
- Batch processing capabilities to ingest entire directories of historical bid documents simultaneously.
- Automated compliance verification that checks file naming conventions, page counts, and mandatory section presence.
- Semantic similarity engine to cross-reference current bids with past winning proposals.
SKILL.md
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