Skill2 repo starsupdated today
prospect
The prospect skill transforms an ideal customer profile description into a ranked list of qualified leads with phone numbers. It parses natural language requirements into structured company and contact filters, resolves those filters to canonical values through lookup calls, searches for matching companies and contacts, and enriches top results with contact details. Use this skill when building targeted outreach campaigns that require accurate filtering across industry, company size, job titles, and other criteria before phone enrichment.
Install in Claude Code
Copygit clone --depth 1 https://github.com/lusha-oss/lusha-mcp-plugin /tmp/prospect && cp -r /tmp/prospect/skills/prospect ~/.claude/skills/prospectThen start a new Claude Code session; the skill loads automatically.
Definition
SKILL.md
# Prospect Go from an ICP description to a ranked, phone-enriched lead list. Filters are resolved before search — never guess filter values. ## Step 1 — Parse the ICP Extract structured filters from the user's natural language description. Some filters take free-form text directly; others must be resolved to canonical values first. **Contact filters (`prospecting_contact_search`):** - Job titles → pass directly as `jobTitles` (free-form strings, e.g. "VP of Sales"). No resolution call needed. - Department / seniority → resolve via `prospecting_contact_filters` (type: `departments`, `seniority`). Use these for broad role targeting when a specific title isn't given. - Country → resolve via `prospecting_contact_filters` (type: `all_countries`); Location → type: `locations` (requires `locationSearchText`). **Company filters (`prospecting_company_search`):** - Industry → resolve via `prospecting_company_filters` (type: `industries_labels`) - Size → resolve via `prospecting_company_filters` (type: `sizes`) - Revenue → resolve via `prospecting_company_filters` (type: `revenues`) - Location → resolve via `prospecting_company_filters` (type: `locations`, requires `q`) - Tech stack → resolve via `prospecting_company_filters` (type: `technologies`, requires `q`) - Buying intent → resolve via `prospecting_company_filters` (type: `intent_topics`) Resolve every non-title filter to canonical values before searching — passing raw natural-language strings as structured filter values is the most common cause of search failures. Each `prospecting_*_filters` call resolves one filter type; run the independent lookups in parallel. If the ICP is too vague to resolve (no title, no industry, no company size), ask one clarifying question before proceeding. At minimum, a title or department and at least one company-level constraint are required. See `references/filter-guide.md` for filter resolution details. ## Step 2 — Search Companies Use `prospecting_company_search` with resolved company filters. Request up to 25 results. This scopes the contact search to qualified accounts. If the user only specified contact-level criteria (no company filters), skip this step and go directly to Step 3. ## Step 3 — Search Contacts Use `prospecting_contact_search` with resolved contact filters. Scope to the company results from Step 2 where applicable. Request up to 25 results. ## Step 4 — Enrich Top Results Search results are previews — they carry no phones/emails but include a `canReveal[]` list per contact showing which fields can be revealed and their per-field credit cost in `canReveal[].credits`. Use `prospecting_contact_enrich` with the contact `id`s to reveal phones and email. Pass `reveal` set from the results' `canReveal[].field` to control exactly which fields (and credits) you pay for. Up to **50** contacts per call — split larger sets across calls. Before enriching, sum the `canReveal[].credits` for the fields you'll reveal, state the total to the user, and wait for confirmation on large batches. Use `account_usage` first if the user wants to confirm their balance covers it. ## Step 5 — Present the Lead List ### Filters Applied Show the user exactly what was used so they can verify: | Filter | Value | |--------|-------| | ... | ... | ### Lead List | # | Name | Title | Company | Industry | Size | Direct Phone | Mobile | Email | Intent Signal | |---|------|-------|---------|----------|------|-------------|--------|-------|---------------| - Surface direct phone and mobile as separate columns — do not merge or hide them - Mark missing phone numbers with `—` not blank cells - Include intent signal column only if `intent_topics` filter was used ### Summary - Results found: X (showing top Y) - Contacts with verified phone: Z - Credits consumed: N ## Step 6 — Offer Next Actions 1. **Refine** — adjust filters and re-run 2. **Add intent filter** — narrow to companies actively researching a topic 3. **Add tech stack filter** — narrow to companies using a specific technology 4. **Run signal-prospect** — cross this list against current buying signals 5. **Export** — format as CSV for copy-paste
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