Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Parallel Enrichment
Bulk data enrichment via Parallel API. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data.
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Bulk data enrichment via Parallel API. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
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- Review SKILL.md after the package is downloaded.
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New install
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
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- NormallyGaussian
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Documentation
Parallel Enrichment
Bulk data enrichment that adds web-sourced fields to lists of companies, people, or products. Describe what you want in natural language.
When to Use
Trigger this skill when the user asks for: "enrich this list with...", "add CEO names to...", "find funding for these companies..." "look up contact info for...", "get LinkedIn profiles for..." Bulk data operations on CSV files or lists Adding web-sourced columns to existing datasets Lead enrichment, company research, product comparison
Quick Start
# Inline data parallel-cli enrich run \ --data '[{"company": "Google"}, {"company": "Microsoft"}]' \ --intent "CEO name and founding year" \ --target output.csv # CSV file parallel-cli enrich run \ --source-type csv --source input.csv \ --target output.csv \ --intent "CEO name and founding year"
Basic Usage
parallel-cli enrich run [options] Note: There is no --json flag for enrich. Results are written to the target file.
Common Flags
FlagDescription--data "<json>"Inline JSON array of records--source-type csvSource file type--source <path>Input CSV file path--target <path>Output CSV file path--source-columns "<json>"Describe input columns--enriched-columns "<json>"Specify output columns--intent "<description>"Natural language description of what to find--processor <tier>Processing tier (see table below)
Processor Tiers
ProcessorUse Caselite-fastSimple lookupsbase-fastBasic enrichmentcore-fastStandard enrichmentpro-fastDeep enrichment (default)ultra-fastComplex multi-source enrichment
Examples
Inline data enrichment: parallel-cli enrich run \ --data '[{"company": "Stripe"}, {"company": "Square"}, {"company": "Adyen"}]' \ --intent "CEO name, headquarters city, and latest funding round" \ --target ./companies-enriched.csv CSV file enrichment: parallel-cli enrich run \ --source-type csv \ --source ./leads.csv \ --target ./leads-enriched.csv \ --source-columns '[{"name": "company_name", "description": "Company name"}]' \ --intent "Find CEO name, company size, and LinkedIn company page URL" With explicit output columns: parallel-cli enrich run \ --data '[{"name": "Sam Altman"}, {"name": "Satya Nadella"}]' \ --source-columns '[{"name": "name", "description": "Person full name"}]' \ --enriched-columns '[ {"name": "current_company", "description": "Current company/employer"}, {"name": "title", "description": "Current job title"}, {"name": "twitter", "description": "Twitter/X handle"} ]' \ --target ./people-enriched.csv Using AI to suggest columns: # First, get AI suggestions parallel-cli enrich suggest \ --source-type csv \ --source ./companies.csv \ --intent "competitor analysis data" # Then run with suggested columns parallel-cli enrich run \ --source-type csv \ --source ./companies.csv \ --target ./companies-analysis.csv \ --intent "competitor analysis: market position, key products, recent news"
Intent Description
Write 1-2 sentences describing: What specific fields you want to add Context about the data (B2B companies, tech startups, etc.) Any constraints (recent data, specific sources) Good: --intent "Find CEO name, total funding raised, and number of employees for B2B SaaS companies" Poor: --intent "Find stuff about these companies"
Source Column Descriptions
When using --source-columns, provide context: [ {"name": "company", "description": "Company name, may include Inc/LLC suffix"}, {"name": "website", "description": "Company website URL, may be partial"} ]
Response Format
The CLI outputs: A monitoring URL to track progress Status updates as rows are processed Final output written to target CSV The target CSV contains: All original columns from the source New enriched columns as specified A _parallel_status column indicating success/failure per row
Output Handling
After enrichment completes: Report the number of rows enriched Preview the first few rows: head -6 output.csv Share the full path to the output file Note any rows that failed enrichment
Configuration File
For complex enrichments, use a YAML config: # enrich-config.yaml source: type: csv path: ./input.csv columns: - name: company_name description: "Company legal name" - name: website description: "Company website URL" target: type: csv path: ./output.csv enriched_columns: - name: ceo_name description: "Current CEO full name" - name: employee_count description: "Approximate number of employees" - name: funding_total description: "Total funding raised in USD" processor: pro-fast Then run: parallel-cli enrich run enrich-config.yaml
Running Out of Context?
For large enrichments, save results and use sessions_spawn: parallel-cli enrich run --source-type csv --source input.csv --target /tmp/enriched-<topic>.csv --intent "..." Then spawn a sub-agent: { "tool": "sessions_spawn", "task": "Read /tmp/enriched-<topic>.csv and summarize the results. Report row count, success rate, and preview first 5 rows.", "label": "enrich-summary" }
Error Handling
Exit CodeMeaning0Success1Unexpected error (network, parse)2Invalid arguments3API error (non-2xx) Common issues: Row failures: Check _parallel_status column in output Timeout: Use smaller batches or lower processor tier Rate limits: Add delays between large enrichments
Prerequisites
Get an API key at parallel.ai Install the CLI: curl -fsSL https://parallel.ai/install.sh | bash export PARALLEL_API_KEY=your-key
References
API Docs Enrichment API Reference
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md