An advanced market intelligence and commercial data analytics skill designed to reverse-engineer any enterprise's public bidding success, revenue streams, and core government or enterprise customer profiles.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install core-bid-winner-profiler
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 core-bid-winner-profiler 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 Core Bid Winner Profiler?
The Core Bid Winner Profiler is a sophisticated business intelligence tool engineered for Openclaw Skills ecosystems. It acts as an automated commercial data analyst specialized in government and enterprise procurement rules, market penetration strategies, and Go-To-Market (GTM) analysis. When activated, the skill deeply investigates target enterprises to discover what types of public or private projects they win, whose budget they leverage, and what their actual implementation capabilities and cash flow health look like.
By converting raw, unstructured procurement announcements into structured, high-fidelity insights, this skill removes the ambiguity from competitive intelligence. It empowers organizations to evaluate the real fiscal and operational baseline of market competitors, target prospects, or prospective investment options through structured bidding evaluation workflows.
Core Bid Winner Profiler Use Cases
- Investment Due Diligence: Assess an enterprise's structural growth sustainability and identity high-risk dependencies on single large clients before committing capital.
- Mergers & Acquisitions (M&A) Audit: Verify real corporate revenue baselines and evaluate key client quality through official public bidding histories.
- Competitive Landscape Analysis: Uncover a competitor's strategic market penetration workflows, regional strongholds, and pricing patterns.
- Strategic Account Benchmarking: Discover high-performing proxy accounts and baseline customer case studies to direct internal sales and GTM strategy.
How Core Bid Winner Profiler Works
- Entity Extraction & Standardization: Parses the user command to isolate the absolute official registered company name, cross-referencing short names against database records to guarantee match accuracy.
- Strategic Web Retrieval: Deploys programmatic search strings across public procurement clearinghouses, official government bidding disclosure platforms, and fiscal news engines using targeted operators like
ANDandORlogic. - Structured Data Extraction: Processes unstructured web content to rigorously isolate and map key fields, including procurement entity name, final winning bid amount, and core project scope.
- Client Profile Clustering: Groups client data programmatically into systemic verticals (such as Public Safety, Transportation, Municipal, or State-Owned Enterprises) to isolate the core revenue architecture.
- Geographical & GTM Inference: Calculates regional distribution patterns to pinpoint active regional strongholds, newly penetrated target territories, and future geographic expansions.
- Financial Health Synthesis: Analyzes average deal size, revenue concentration risks among the top 3 clients, and bidding mechanics to compile a formal analysis report.
Core Bid Winner Profiler Setup
Ensure your environment is running the openclaw agent ecosystem with active internet search extensions enabled.
Clone or include the component inside your local skills library directory:
# Initialize the profile configuration inside your system directory
openclaw skill install core-bid-winner-profiler
# Confirm that necessary prerequisite entity resolution modules are present
python -c "import search_ent_simple"
Configure your environment variables to allow search capability access to authoritative corporate registry databases and major public procurement aggregators.
Core Bid Winner Profiler Data Schema & Taxonomy
Input Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
company_name |
string | Yes | The absolute official registered corporate name to maximize dataset matching accuracy. |
time_range |
int | No | The search horizon in months. Defaults to 12 months if unassigned. |
min_amount |
string | No | Lower-bound monetary threshold filter (e.g., "100万", "1000万"). No lower boundary by default. |
bid_type |
string | No | Focus sector classification: all, government, or enterprise. Defaults to all. |
Output Architecture (Core Bid Analysis Report)
The data generated by this Openclaw Skills asset maps into five core content blocks:
- Corporate Baseline Records: Company name, unified social credit identifier, and defined industry vertical.
- Bidding Record Ledger: A structured compilation tracking matching timeframe, buyer entity, normalized winning value, project designation, and asset classification (hardware, software, services, systems integration).
- Buyer Archetype Mapping: Percentages showing total value share per buyer sector, plus typical key account names.
- Regional Penetration Mapping: Geographic distribution tables grouping total values by province/city, identifying established territory strongholds versus new market entry zones.
- Deal Size & Flow Health Index: Average contract size calculations, dependency indexes for the top 3 clients, and cash flow predictability indicators based on historical seasonal trends.
Core Bid Winner Profiler Advanced Features
- Cross-Competitor Benchmarking: Input multiple target enterprise entities simultaneously to output parallel comparative reports analyzing overlapping accounts and relative contract capture sizing.
- Bidding Trend Graphing: Generates multi-quarter text-based structural charts mapping volume trends and shifting average deal sizes over arbitrary historical ranges.
- Concentration Risk Alerting: Programmatically highlights structural over-reliance on single buyers or high-concentration single-source awards, flagging hidden regulatory compliance risks or supply vulnerabilities.
- Automated Fallback Exception Handling: Intelligently handles hidden contract pricing by marking items as undisclosed to protect statistical calculations without losing the project tracking records.
SKILL.md
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