Cold Outreach Skill

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name: cold-outreach-hunter description: Meta-skill for orchestrating Apollo API, LinkedIn API, YC Cold Outreach, and MachFive Cold Email into a complete B2B cold outreach pipeline. Use when the user wants end-to-end lead sourcing, enrichment, personalized copy strategy, and generation-ready outreach sequences with strict quality and safety gates. homepage: https://clawhub.ai user-invocable: true disable-model-invocation: false metadata: {"openclaw":{"emoji":"dart","requires":{"bins":["python3","npx"],"env":["MATON_API_KEY","MACHFIVE_API_KEY"],"config":[]},"note":"Requires local installation of apollo-api, linkedin-api, yc-cold-outreach, and cold-email."}}

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Purpose

Run a full B2B cold outreach workflow from ICP definition to sequence-ready output.

Primary objective:

Identify high-fit leads.

Enrich context for personalization.

Produce concise, non-salesy, high-response outreach sequences.

Return execution-ready assets for external sending/scheduling systems.

This is an orchestration skill. It coordinates upstream skills; it does not replace them.

Required Installed Skills

apollo-api (inspected latest: 1.0.5)

linkedin-api (inspected latest: 1.0.2)

yc-cold-outreach (inspected latest: 1.0.1)

cold-email (MachFive Cold Email, inspected latest: 1.0.5)

Install/update with ClawHub:

npx -y clawhub@latest install apollo-api
npx -y clawhub@latest install linkedin-api
npx -y clawhub@latest install yc-cold-outreach
npx -y clawhub@latest install cold-email
npx -y clawhub@latest update --all

Verify availability:

npx -y clawhub@latest list

If any required skill is missing, stop and report exact install commands.

Required Credentials

MATON_API_KEY for apollo-api and linkedin-api (Maton gateway)

MACHFIVE_API_KEY for cold-email

Preflight checks:

echo "$MATON_API_KEY" | wc -c
echo "$MACHFIVE_API_KEY" | wc -c

If either key is missing or empty, stop before lead processing.

Job Context Template

Collect these inputs before execution:

offer: what is being sold (example: design service)

icp_title: target role (example: CMO)

icp_industry: target industry (example: SaaS)

icp_location: target location (example: Berlin)

lead_count_target (example: 50)

campaign_goal: reply, meeting, referral, audit request, etc.

proof_points: case studies, metrics, social proof

tone_constraints: plain-English, short, non-salesy

machfive_campaign (campaign ID or campaign name to resolve)

execution_mode: draft-only or generation-ready

Do not start writing copy until these are explicit.

Tool Responsibilities

Apollo API (apollo-api)

Use for lead discovery and basic enrichment.

Operationally relevant behavior from inspected skill:

Search people: POST /apollo/v1/mixed_people/api_search

Search filters include:

- q_person_title - person_locations - q_organization_name - q_keywords

Enrich person by email or LinkedIn URL:

- POST /apollo/v1/people/match

Supports pagination via page and per_page.

Uses Maton gateway and optional Maton-Connection header.

Primary output of this stage:

initial lead list with role/company/email/linkedin_url (when available)

LinkedIn API (linkedin-api)

Use for LinkedIn-side context where accessible through provided endpoints.

Operationally relevant behavior from inspected skill:

Authenticated profile/user info endpoints (for connected account context).

Content/posting APIs (ugcPosts) and organization post/stat APIs.

Requires MATON_API_KEY and LinkedIn protocol headers.

Important boundary:

The inspected skill is not a generic scraper for arbitrary third-party personal profiles and recent personal posts.

If a workflow requires deep per-lead personal-post enrichment, mark that as additional-tool-required.

YC Cold Outreach (yc-cold-outreach)

Use as writing strategy/critique framework, not as a transport API.

Core principles to enforce:

single goal per email

human tone

deep personalization (not just token replacement)

brevity/mobile readability

credibility and proof

reader-centric language

clear CTA

MachFive Cold Email (cold-email)

Use for sequence generation from prepared lead records.

Operationally relevant behavior from inspected skill:

Campaign required (campaign_id mandatory for generate endpoints).

Single lead sync generation (/generate) can take minutes; use long timeout.

Batch async generation (/generate-batch) returns list_id; poll list status; export when complete.

Lead email is required.

Supports structured sequence output with subject/body per step.

Canonical Workflow

Stage 1: Build lead universe (Apollo)

1. Query Apollo for ICP-constrained leads (example: CMO + SaaS + Berlin). 2. Page until lead_count_target or quality threshold is reached. 3. Normalize each lead record to required fields. 4. Drop records without email if generation-ready mode is requested (MachFive requires email).

Recommended normalized lead schema:

{
  "lead_id": "apollo-or-derived-id",
  "name": "Anna Example",
  "title": "Chief Marketing Officer",
  "company": "Startup GmbH",
  "location": "Berlin",
  "email": "anna@startup.com",
  "linkedin_url": "https://linkedin.com/in/...",
  "source": "apollo-api"
}

Stage 2: Enrich personalization context

1. Attempt LinkedIn/API enrichment within supported endpoints. 2. If direct personal-post signal is unavailable, keep the context slot explicit as not_available. 3. Optionally enrich from Apollo fields (company, role, keywords, domain context) to avoid fake personalization.

Personalization object per lead:

{
  "icebreaker": "not_available_or_verified_fact",
  "pain_hypothesis": "Likely CRO bottleneck in paid landing pages",
  "proof_hook": "Helped X improve conversion by Y%",
  "confidence": 0.0
}

Hard rule:

Never invent a post, interest, or quote.

Stage 3: Message strategy (YC framework)

For each lead, create a strategy brief before generating copy:

Problem: what specific pain this role likely has

Solution: what your offer solves

Proof: one concrete metric/client signal

CTA: one low-friction next step

Apply YC constraints:

one ask

short/mobile-first

human language

personalization grounded in verifiable context

Stage 4: Sequence generation (MachFive)

1. Resolve campaign ID first (GET /api/v1/campaigns) if not provided. 2. Submit leads with required email field. 3. Prefer batch for many leads; poll until completion. 4. Export JSON result and map sequences back to lead IDs.

Required generation payload hygiene:

include name, title, company, email

include linkedin_url and company_website when available

set email_count intentionally (usually 3)

use approved CTA set aligned with campaign goal

Stage 5: QA and decision gate

Before declaring output ready, validate each sequence:

personalization factuality check

YC rubric check (human, concise, one CTA)

token insertion sanity (name/company/title correct)

prohibited claims check (no fabricated proof)

Any failed sequence must be flagged needs_revision.

Stage 6: Scheduling and send handoff

This meta-skill outputs send-ready recommendations, not direct send automation.

If user asks for timing optimization (for example Tuesday 10:00), return it as a scheduling recommendation field and handoff plan.

Example handoff object:

{
  "lead_id": "...",
  "sequence_status": "approved",
  "suggested_send_time_local": "Tuesday 10:00",
  "timezone": "Europe/Berlin",
  "send_system": "external",
  "notes": "Timing is recommendation-only; execution tool must schedule/send."
}

Causal Chain (Scenario Mapping)

For the scenario "sell design services to startup marketing leaders":

1. Apollo returns target leads (example target: 50 CMOs in Berlin SaaS). 2. LinkedIn/API enrichment attempts to add usable context per lead. 3. YC framework converts lead context into a concise Problem → Solution → Proof → CTA angle. 4. MachFive generates multi-step sequences with validated variables. 5. Agent outputs: - approved sequences - quality score per lead - scheduling recommendation (example: Tuesday 10:00 local)

Output Contract

Always return these sections:

LeadSummary

- requested vs qualified lead count - rejection reasons (missing email, poor fit, duplicate)

EnrichmentSummary

- fields successfully enriched - unavailable fields and why

SequencePackage

- one object per lead with subjects/bodies by step - QA status (approved or needs_revision)

ExecutionPlan

- send-time recommendation - required external sender/scheduler - blockers (missing campaign, missing API key, missing email)

Guardrails

Never fabricate personalization facts.

Never claim a lead posted something unless sourced and verifiable.

Do not proceed to MachFive generation without campaign ID resolution.

Do not mark sequence approved when CTA is unclear or multiple asks exist.

Keep language non-manipulative and compliant with outreach policies.

Failure Handling

Missing MATON_API_KEY: stop Apollo/LinkedIn stages.

Missing MACHFIVE_API_KEY: stop generation stage and return draft-only strategy.

Missing campaign ID: list campaigns and request explicit selection.

Batch timeout/partial output: continue via list status + export recovery flow.

Insufficient lead quality: return reduced high-quality set instead of forcing volume.

Known Limits from Inspected Upstream Skills

linkedin-api inspected capability set is not equivalent to unrestricted scraping of arbitrary personal lead activity.

cold-email generates sequences but does not itself guarantee outbound send scheduling/execution.

apollo-api provides search/enrichment primitives; email deliverability validation beyond provider fields may require extra tooling.

Treat these as explicit constraints in planning and reporting.