ocean-io海洋IO

Overview

This skill connects your OpenClaw agent to Ocean.io's B2B intelligence platform. Use it to build prospect lists, enrich accounts, find lookalike companies, and surface the right contacts — all from natural language commands.

Ocean.io covers 60M+ companies and 200M+ people. Credits are consumed at 0.2 per record for both searches and exports.

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When to use this skill

Activate Ocean.io when the user wants to:

• - Find companies similar to existing customers ("lookalike" search)
• Build a prospect list filtered by industry, size, location, or tech stack
• Identify decision-makers at target accounts by title, department, or seniority
• Export a contact or company list to CSV for use in outreach tools
• Check what fields are available before building a search

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Tools

search_companies

Find companies matching ICP criteria or similar to a set of seed domains. Use lookalike_domains when the user wants to replicate their best customers.

Key filters available:

• - lookalikeDomains — up to 10 seed domains to find similar companies
• INLINECODE3 — "precise" (same product/service) or "broad" (same industry)
• INLINECODE6, industryCategories — firmographic segmentation
• INLINECODE8 — e.g. INLINECODE9
• INLINECODE10 / otherLocations — HQ country or office presence
• INLINECODE12 / technologies.categories — tech stack filters
• INLINECODE14 — growth signal over 3, 6, or 12 months
• INLINECODE15 — type, amount, and date of last funding
• INLINECODE16 — revenue band filter
• INLINECODE17 — monthly visits/views range
• INLINECODE18 — exclude known customers or competitors

Always check list_company_fields if the user asks what data is available.

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search_people

Find people by job title, seniority, department, or company criteria. The people_fields parameter is required — always specify what to return.

Key filters available:

• - jobTitleKeywords — keyword match on title (allOf / anyOf / noneOf)
• INLINECODE23 — Owner, Founder, C-Level, VP, Head, Director, Manager, Other
• INLINECODE24 — Sales, Marketing and Advertising, Engineering, Product, etc.
• INLINECODE25 / cities / states — geographic filters
• INLINECODE28 — nest any search_companies filters to target people at specific accounts
• INLINECODE30 — recently promoted/hired contacts (format: "YYYY-MM")
• INLINECODE31 — find people similar to a given LinkedIn profile
• INLINECODE32 — filter by LinkedIn-listed skills
• INLINECODE33 — filter by LinkedIn connection count

Always check list_people_fields if the user asks what data can be returned.

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export_companies

Export company records to a CSV file. Returns a download URL for the generated file.

⚠️ Costs credits: 0.2 credits per successfully exported company. Always confirm the number of records and estimated credit cost with the user before calling this tool.

Input: array of company domains. Accepts up to 10,000 domains per request.

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export_people

Export people records to a CSV file. Returns a download URL for the generated file.

⚠️ Costs credits: 0.2 credits per successfully exported person. Always confirm the number of records and estimated credit cost with the user before calling this tool.

Input: array of LinkedIn handles or URLs (from search_people results). Accepts up to 10,000 per request.

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list_company_fields

Returns all available fields for company records. Output is static — call once per session and cache the result. Do not call again if already retrieved. Use when the user asks "what data does Ocean.io have on companies?"

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list_people_fields

Returns all available fields for people records. Output is static — call once per session and cache the result. Use when the user asks "what fields can I get for contacts?"

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list_industries / list_linkedin_industries

Returns valid industry values for filters. Output is static — call once per session and cache the result. Always validate industry names against this list before passing them to search filters.

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Example workflows

ICP lookalike prospecting

"Find 20 companies similar to stripe.com and shopify.com, B2B SaaS, 50-500 employees, US-based."

1. 1. Call search_companies with lookalikeDomains: ["stripe.com", "shopify.com"],

companySizes: ["51-200", "201-500"], primaryLocations: { includeCountries: ["us"] }.

1. 2. Present results as a table (name, domain, size, industry, country).
2. Confirm credit cost (N × 0.2) before calling export_companies.

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Finding decision-makers at target accounts

"Find VP of Sales or Head of Revenue at these 10 companies."

1. 1. Call search_people with jobTitleKeywords: { anyOf: ["VP of Sales", "Head of Revenue"] },

seniorities: ["VP", "Head"], company_filters: { includeDomains: [...] }, people_fields: ["name", "jobTitle", "linkedinUrl", "country", "departments"].

1. 2. Display results as a table.
2. Offer to export — confirm credit cost before calling export_people.

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Trigger-based prospecting (recently funded)

"Find Series A or B SaaS companies that raised funding in the last 6 months."

1. 1. Call search_companies with fundingRound: { types: ["Series A", "Series B"], date: { from: "<6 months ago>" } }.
2. Optionally layer in industry/size filters if the user specifies an ICP.
3. Suggest following up with search_people to find the relevant contacts at those accounts.

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Hiring signal prospecting

"Find companies in the sales tech space that are rapidly growing their Sales department."

1. 1. Call search_companies with departmentHeadcountGrowth targeting the Sales department

with positive growth over the last 6 months.

1. 2. Cross-reference with industry or tech stack filters to narrow to ICP.

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Full account + contact workflow with export

"Find Chicago-headquartered companies similar to pandadoc.com and export them to CSV."

1. 1. Call search_companies with lookalikeDomains: ["pandadoc.com"], primaryLocations: { includeCountries: ["us"] }, and a city filter for Chicago.
2. Present results as a table (name, domain, description).
3. State: "This export will consume X credits (N companies × 0.2). Confirm?"
4. On confirmation, call export_companies and return the download URL to the user.

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Credit awareness

All operations consume credits at 0.2 credits per record — this applies to both search results and exports. Before any search, state the estimated credit cost (num_results × 0.2). Before any export, confirm: "This will export N records at 0.2 credits each = X credits total. Confirm?"

Never call export_companies or export_people without explicit user confirmation.

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Tips

• - Use companyMatchingMode: "precise" for tight lookalikes (same product category).

Use "broad" when the user wants a wider net (same industry vertical).

• - Combine search_companies + search_people for full account + contact workflows:

find the companies first, then pass their domains into company_filters.includeDomains on search_people.

• - changedPositionAfter is powerful for timing outreach — a newly hired VP of Sales

is actively building their stack.

• - Both search_companies and search_people return paginated results. After presenting the first page, offer to load more. Pass the searchAfter token from the last result into the next call to fetch the next page.
• For pagination, pass the searchAfter value from previous results back into the next call.