Systems Lab

Agent skill

lead-dossier

activeNeeds a keyActs undeclared739 words

From ericosiu/ai-marketing-skills · 21 skills · 3,449 · pushed 2026-08-16

What it does when it runs

Read from the skill and the 8 files bundled beside it. A skill’s own description is written to be selected by an agent, so it describes the job and not the dependencies.

Keys and connectors you must supply
  • API_KEY
  • BUILTWITH_API_KEY
  • CAMPAIGN_TOOL_API_KEY
  • CRM_API_KEY
  • EMAIL_VALIDATION_API_KEY
  • LEAD_SOURCE_API_KEY
  • YOUR_KEY
Hosts it reaches
  • api.apollo.io
  • api.builtwith.com
  • api.hubapi.com
  • api.your-campaign-tool.com
  • api.your-email-provider.com
  • api.your-provider.com
  • levelingup.beehiiv.com
  • singlebrain.com
  • www.singlegrain.com
Tool permissions it declares
No allowed-tools in the frontmatter. It does act, so it runs under whatever permissions your session already grants.
Actions present in the files
shellwrites files

Ask about lead-dossier

Opens your assistant with this page's verified links already in the prompt.

Is this safe to install?ClaudeChatGPT
Adapt it to my stackClaudeChatGPT
What else do I need for it to workClaudeChatGPT
Rather ask a human? Talk to Cheetah
git clone --depth 1 --filter=blob:none --sparse https://github.com/ericosiu/ai-marketing-skills.git /tmp/ai-marketing-skills
git -C /tmp/ai-marketing-skills sparse-checkout set "lead-dossier"
mkdir -p ~/.claude/skills/lead-dossier
cp -R "/tmp/ai-marketing-skills/lead-dossier/." ~/.claude/skills/lead-dossier/

Picked up without a restart. A project skill of the same name is shadowed by your personal one. For one repository only, swap ~/.claude/skills for .claude/skills. Claude Code docs ↗

The folder is the same in every client that implements the format — 46 of them — so if yours is not above, only the destination changes.

Before you install: this skill will not complete its job on a bare agent. It needs API_KEY, BUILTWITH_API_KEY, CAMPAIGN_TOOL_API_KEY, CRM_API_KEY, EMAIL_VALIDATION_API_KEY, LEAD_SOURCE_API_KEY, YOUR_KEY, which you have to obtain separately.

Reproduced in full from ericosiu/ai-marketing-skills/blob/2eb0f34edb8d6111ca8b2930fed92413c9af7002/lead-dossier/SKILL.md, which is licensed MIT (repository). 739 words, 18 headings.

name: lead-dossier description: > Multi-source account research, cascade enrichment, and lead pipeline. Combines website scraping, tech stack detection, CRM enrichment, hiring/news signals into structured dossiers. Includes full lead sourcing pipeline: search → verify → dedupe → upload. Triggers on: "research account", "build dossier", "enrich leads", "lead pipeline", "source leads", "prospect research", "account intel", "cascade enrichment", "lead scoring", "find leads", "verify emails", "upload leads".

Lead Dossier Skill

Multi-source account research and lead enrichment pipeline for AI coding assistants.

Prerequisites

  • Python 3.9+ with requests installed
  • API keys configured as environment variables (see .env.example)
  • Optional: CRM access for contact/company enrichment

Environment Variables

All API keys are configured via environment variables. Copy .env.example to .env:

VariableDescription
LEAD_SOURCE_API_KEYPeople/company search API
EMAIL_VALIDATION_API_KEYEmail verification service
EMAIL_VALIDATION_API_URLEmail verification endpoint
CAMPAIGN_TOOL_API_KEYOutbound campaign platform
CRM_API_KEYCRM API key
CRM_BASE_URLCRM API base URL
BUILTWITH_API_KEYBuiltWith tech detection (free tier works)

Workflow 1: Account Research

Use when asked to research a company or build a prospect dossier.

Collect Parameters

ParameterRequiredExample
DomainYesacme.com
Company nameNoAcme Corp
Contact nameNoJane Doe
Contact titleNoVP Marketing

Run Research

python3 scripts/account-researcher.py --domain acme.com --company "Acme Corp"

For batch research:

python3 scripts/account-researcher.py prospects.json

Results are cached for 7 days in data/account-research/.

Output Format

The engine produces a structured JSON dossier with:

  • Website analysis (title, description, body snippet, marketing gaps)
  • Tech stack (CRM, marketing tools, enterprise signals)
  • Hiring signals (growth indicators)
  • News/funding signals
  • 3-5 sentence research brief

Workflow 2: Cascade Enrichment

Use when enriching a list of prospects with verified email addresses.

Prepare Config

Create data/enrichment-config.json:

{
  "email_validation_api_key": "YOUR_KEY",
  "email_validation_api_url": "https://api.your-provider.com/v1/people/email-finder",
  "email_validation_timeout_seconds": 10,
  "fallback_tag": "linkedin-outreach-only"
}

Run Enrichment

python3 scripts/cascade-enricher.py input.json output.json

Waterfall logic:

  1. Has email from primary source? → Done
  2. Try email finder API → Found? → Done
  3. Has LinkedIn URL? → Tag as fallback
  4. None → Tag as no-contact

Workflow 3: Full Lead Pipeline

Use when sourcing, verifying, and uploading leads end-to-end.

Collect Parameters

ParameterRequiredExample
TitlesYesVP Marketing, CMO
IndustriesYesMarketing, SaaS
Company sizeYes11-50, 51-200
LocationsYesUnited States
Campaign IDYesCampaign UUID
VolumeYes500

Run Pipeline

python3 scripts/lead-pipeline.py \
  --source-api-key "$LEAD_SOURCE_API_KEY" \
  --validation-api-key "$EMAIL_VALIDATION_API_KEY" \
  --campaign-api-key "$CAMPAIGN_TOOL_API_KEY" \
  --titles "VP Marketing,CMO,Head of Growth" \
  --industries "Marketing,Advertising" \
  --company-size "11,50" \
  --locations "United States" \
  --campaign-id "CAMPAIGN_UUID" \
  --volume 500 \
  --output-dir ./data/pipeline-runs/

Optional flags:

  • --exclude-file /path/to/burned-emails.csv — additional exclusion list
  • --dry-run — run everything except the final upload
  • --keywords "SaaS,B2B" — additional search keywords

Review Output

Pipeline saves a JSON run log to the output directory with full stats:

  • Sourced count, verification rate, dedup stats, upload results
  • Complete list of leads processed

Workflow 4: Real-Time Lead Enrichment

Use for enriching inbound leads from webhooks, forms, or CRM triggers.

Run Enricher

python3 scripts/lead-enricher.py [--dry-run] [--backfill N]

The enricher:

  1. Parses inbound lead data (website forms, voice agent calls, etc.)
  2. Looks up contact and company in CRM
  3. Runs account research for context
  4. Builds an enriched lead card with all available data

Safety Rules

  1. Never upload unverified leads — every email must pass validation
  2. Always deduplicate — check existing contacts before uploading
  3. Log everything — every run produces an auditable JSON log
  4. Rate limit aware — built-in delays and exponential backoff
  5. Idempotent — safe to re-run; duplicates are caught by dedup step
  6. Security gates — scan all inbound web content before processing

Troubleshooting

  • Search API returns no results: Check title/industry spelling; try broader criteria
  • Email validation 429s: Script handles with backoff; if persistent, reduce volume
  • Campaign tool silent failures: Some APIs silently block at high request rates; scripts include batch delays
  • Cache stale: Delete files in data/account-research/ to force refresh

Files bundled with it

These load only when the skill asks for them, so they cost nothing until it runs.

Other skills for the same job

Different authors, same problem. Matched on the words in the skill name, across every library in the catalogue except this one.

Need help setting it up?

This page tells you what lead-dossier does and what it needs. Cheetah builds the agent setup it runs inside: data, CRM, sequencing and the guardrails.

Book a call →

The directory stays free. There is nothing gated behind this.