sales-skrapp
Skrapp.io platform help — B2B email finder and datan enrichment with 200M+ contacts and 20M+ company profiles. Use when you can't find a prospect's email, LinkedIn profiles don't show contact info, your CSV of leads is missing emails and firmographics, email verification is bouncing too many contacts, the Chrome extension isn't pulling data from LinkedIn, or the Skrapp API isn't returning results. Do NOT use for general enrichment strategy (use /sales-enrich), deliverability/warmup (use /sales-deliverability), or building prospect lists strategy (use /sales-prospect-list).
What this skill does
# Skrapp.io Platform Help Help the user with Skrapp.io platform questions — from Email Finder and Lead Finder through Data Enrichment, AI Fields, Email Verification, Chrome Extension, Company Search, and CRM Integrations. Skrapp.io is a Singapore-based (also Casablanca, Morocco) B2B email finder and datan enrichment platform used by 2M+ professionals with 3B+ email searches processed, offering a REST API and Chrome extension for in-workflow lookup. ## Step 1 — Gather context If `references/learnings.md` exists, read it first for accumulated knowledge. Ask the user: 1. **What area of Skrapp.io do you need help with?** - A) Email Finder — find a verified email by name + company/domain (92% success rate, single or bulk) - B) Lead Finder — search 200M+ B2B contacts with 17+ filters (job title, location, industry, company size, revenue, seniority) - C) Data Enrichment — bulk CSV/Excel upload, auto-map columns, enrich with emails + firmographics (industry, revenue, employee count, location) - D) AI Fields — ML-powered attributes: buying role, seniority, function, gender — auto-populated during enrichment - E) Email Verifier — single + bulk verification (97% accuracy), syntax/format/mailbox checks, disposable detection - F) Chrome Extension — LinkedIn & Sales Navigator email extraction (25 profiles/sec), multi-page enrichment on Pro+ - G) Company Search — find all professionals at a company by domain (20M+ company profiles) - H) CRM Integrations — HubSpot, Salesforce, Zoho, Pipedrive, Outreach, Zapier - I) API — REST API setup, endpoints, authentication - J) Account / Billing — plans, pricing, credits - K) Something else — describe it 2. **What's your role?** - A) Sales / SDR / BDR - B) RevOps / Sales ops - C) Developer / engineer - D) Growth / marketing - E) Recruiter / talent acquisition - F) Other 3. **What are you trying to accomplish?** (describe your specific goal or question) **If the user's request already provides most of this context, skip directly to the relevant step.** Lead with your best-effort answer using reasonable assumptions (stated explicitly), then ask only the most critical 1-2 clarifying questions at the end — don't gate your response behind gathering complete context. Note: If the user needs a specialized skill, route them there with a brief explanation of why that skill is a better fit. ## Step 2 — Route or answer directly If the request maps to a specialized skill, route: - Cross-platform enrichment strategy / multi-tool enrichment -> `/sales-enrich` - Email deliverability / warmup strategy (not Skrapp-specific) -> `/sales-deliverability` - Prospect list building strategy -> `/sales-prospect-list` - Outbound sequence / cadence strategy -> `/sales-cadence` - Connecting Skrapp to other tools via middleware -> `/sales-integration` - Hunter.io-specific questions -> `/sales-hunter` - Apollo-specific questions -> `/sales-apollo` - Prospeo-specific questions -> `/sales-prospeo` - Tomba-specific questions -> `/sales-tomba` - Enrich.so-specific questions -> `/sales-enrichso` - GetProspect-specific questions -> `/sales-getprospect` - Minelead-specific questions -> `/sales-minelead` Otherwise, answer directly from platform knowledge using the reference below. ## Step 3 — Skrapp.io platform reference **Read `references/platform-guide.md`** for detailed module documentation, pricing, integrations, and data model. *You no longer need the platform guide details — focus on the user's specific situation.* ## Step 4 — Actionable guidance Based on the user's specific question: 1. **Finding a specific person's email**: 1. Use the Email Finder: `GET /api/emailFinder?name=Jane+Doe&domain=example.com` with your `X-Access-Key` header 2. Skrapp returns the most likely professional email with verification status — 92% success rate 3. If the email is returned as "accept-all", the domain accepts all addresses so deliverability is uncertain — verify separately or proceed with caution 4. For batch lookups, prepare a CSV with name and domain columns and use the bulk Email Finder (`POST /api/bulk/emailFinder`) 5. No credit is charged if Skrapp cannot find a result or the contact was already looked up — budget only for successful finds 6. Save found contacts to a Skrapp list for organization and CRM sync 2. **Building a filtered prospect list**: 1. Open Lead Finder and apply filters: job title, seniority, industry, location, company size, revenue 2. Skrapp searches 200M+ contacts and returns matching results — each contact reveal costs 1 credit 3. Use AI Fields (Pro+ only) to auto-classify contacts by buying role, seniority, and function — these are added automatically 4. Save results to a Skrapp list using the List Saver feature 5. Sync the list to your CRM (HubSpot, Salesforce, Zoho, Pipedrive, or Outreach) via native integration — sync operates at the list level 6. For very large prospect builds, use multiple filter combinations to stay within credit budget and prioritize highest-value segments first 3. **Enriching a CSV of contacts with email and company data**: 1. Prepare your CSV or Excel file with columns for name and company/domain (Skrapp auto-maps common field names) 2. Upload via Data Enrichment — Skrapp detects and maps columns, then enriches each row with email addresses and firmographics (industry, revenue, employee count, location) 3. Review the auto-mapping before starting — if columns have non-standard names, manually adjust the mapping to avoid mismatches 4. AI Fields (Pro+ only) will auto-populate buying role, seniority, function, and gender for each enriched contact 5. Download the enriched file or save results to a Skrapp list for CRM sync 6. Run Email Verifier on the enriched emails to validate deliverability before outreach — verification is a separate step from enrichment 7. Budget: 1 credit per successfully enriched row — no charge for rows where Skrapp cannot find an email 4. **Extracting emails from LinkedIn with the Chrome Extension**: 1. Install the Skrapp Chrome extension and log in with your Skrapp account 2. Navigate to a LinkedIn profile or Sales Navigator search results page 3. For single profiles: click the Skrapp icon to extract the email — 1 credit per successful extraction 4. For bulk extraction (Pro+ only): on a LinkedIn search results page, use multi-page enrichment to process entire pages at up to 25 profiles/sec 5. Use the List Saver to save extracted contacts directly to a Skrapp list without leaving LinkedIn 6. Auto-connect feature (Pro+) can send connection requests alongside email extraction 7. Be mindful of LinkedIn's own rate limits — even though Skrapp can process 25 profiles/sec, aggressive scraping may trigger LinkedIn restrictions ## Gotchas > *Best-effort from research — review these, especially items about plan-gated features and credit behavior that may have changed since last verified.* 1. **API access requires Enterprise plan (€262/mo) — Professional plan does not include API access.** If you need programmatic access to Skrapp's email finder, verifier, or company info endpoints, you must be on the Enterprise plan. Professional plan users are limited to the web UI, Chrome extension, and CRM integrations. Budget accordingly if you are planning to build an integration or automated workflow that depends on the API. 2. **Credits are not charged for duplicates or invalid results — but this only applies to exact duplicates within your account.** If you look up the same person+domain combination twice, the second lookup is free. Similarly, if Skrapp cannot find an email for a contact, no credit is deducted. However, looking up the same person at a different domain, or re-verifying a previously verified email, may still consume a credit. Track your credit usage in the account dashboard to avoid surprises. 3. **AI Fields (buying role, seniority, function, gender)
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.