Xpersona

Crawler Summary

list-building answer-first brief

Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like finding companies first, then their founders. --- name: list-building description: Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.

Freshness

Last checked 2/25/2026

Best For

list-building is best for path workflows where OpenClaw compatibility matters.

Not Ideal For

Contract metadata is missing or unavailable for deterministic execution.

Evidence Sources Checked

editorial-content, GITHUB OPENCLEW, runtime-metrics, public facts pack

CardFactsSnapshotContractTrust
Claim this agent
Agent DossierGitHubSafety: 89/100

list-building

Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like finding companies first, then their founders. --- name: list-building description: Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like

OpenClawself-declared

Public facts

4

Change events

1

Artifacts

0

Freshness

Feb 25, 2026

Verifiededitorial-contentNo verified compatibility signals

Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.

Trust evidence available

Trust score

Unknown

Compatibility

OpenClaw

Freshness

Feb 25, 2026

Vendor

Hanseflats

Artifacts

0

Benchmarks

0

Last release

Unpublished

Executive Summary

Key links, install path, and a quick operational read before the deeper crawl record.

Verifiededitorial-content

Summary

Capability contract not published. No trust telemetry is available yet. Last updated 2/25/2026.

View Source

Setup snapshot

git clone https://github.com/Hanseflats/list-building-skill.git
  1. 1

    Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.

  2. 2

    Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Evidence Ledger

Everything public we have scraped or crawled about this agent, grouped by evidence type with provenance.

Verifiededitorial-content
Vendor (1)

Vendor

Hanseflats

profilemedium
Observed Feb 25, 2026Source linkProvenance
Compatibility (1)

Protocol compatibility

OpenClaw

contractmedium
Observed Feb 25, 2026Source linkProvenance
Security (1)

Handshake status

UNKNOWN

trustmedium
Observed unknownSource linkProvenance
Integration (1)

Crawlable docs

6 indexed pages on the official domain

search_documentmedium
Observed Apr 15, 2026Source linkProvenance

Release & Crawl Timeline

Merged public release, docs, artifact, benchmark, pricing, and trust refresh events.

Self-declaredagent-index

Docs Update

Docs refreshed: Sign in to GitHub · GitHub

search_documentmedium

Fresh crawlable documentation was indexed for the official domain.

Observed Apr 15, 2026

Artifacts Archive

Extracted files, examples, snippets, parameters, dependencies, permissions, and artifact metadata.

Self-declaredGITHUB OPENCLEW

Extracted files

0

Examples

6

Snippets

0

Languages

typescript

Parameters

Executable Examples

bash

uv pip install ddgs --system  # MUST use 'ddgs' package, NOT 'duckduckgo_search'

python

queries = [
    'site:crunchbase.com "founder" "new york" "software"',
    'site:crunchbase.com "co-founder" "new york" "SaaS"',
    'site:linkedin.com "founder" "new york" "software"',
    'site:linkedin.com "founder & CEO" "new york" "SaaS"',
    'site:linkedin.com "co-founder" "NYC" "software" -jobs -learning',
]

python

from ddgs import DDGS
import time

seen = set()
results = []
for q in queries:
    with DDGS() as ddgs:
        for r in ddgs.text(q, max_results=15):
            if r['href'] not in seen:
                seen.add(r['href'])
                results.append(r)
    time.sleep(2)

text

| # | Name | Title | Company | Location | Profile URL |

text

site:crunchbase.com/organization "{industry}" "{city}"
site:g2.com/products "{category}"
site:clutch.co "{service}" "{city}"

text

site:linkedin.com "{company_name}" "founder" OR "CEO"
site:crunchbase.com/person "{company_name}"

Docs & README

Full documentation captured from public sources, including the complete README when available.

Self-declaredGITHUB OPENCLEW

Docs source

GITHUB OPENCLEW

Editorial quality

ready

Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like finding companies first, then their founders. --- name: list-building description: Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like

Full README

name: list-building description: Build prospect lists using DuckDuckGo dorking when no data enrichment tools (Apollo, Clay, ZoomInfo, etc.) are available. Triggers when users ask to find leads, prospects, founders, decision-makers, build a list, find companies in a niche, or research target accounts. Supports LinkedIn, Crunchbase, G2, Clutch, ProductHunt, and niche directory dorking. Handles multi-step flows like finding companies first, then their founders.

List Building via DDG Dorking

Build targeted prospect lists using DuckDuckGo search dorking. No API keys needed.

Requirements

uv pip install ddgs --system  # MUST use 'ddgs' package, NOT 'duckduckgo_search'

Core Workflow

1. Parse the Request

Extract from the user's ask:

  • WHO: role/title (founder, CEO, VP Sales, etc.)
  • WHERE: location (city, state, country)
  • WHAT: industry/niche (software, SaaS, e-commerce, etc.)
  • HOW MANY: target count (default 20)
  • FILTERS: funding stage, company size, specific platforms, etc.

2. Generate Dork Queries

See references/dork-patterns.md for full pattern library.

Generate 4-8 queries mixing sources and variations. Example for "find 20 founders at software companies in NYC":

queries = [
    'site:crunchbase.com "founder" "new york" "software"',
    'site:crunchbase.com "co-founder" "new york" "SaaS"',
    'site:linkedin.com "founder" "new york" "software"',
    'site:linkedin.com "founder & CEO" "new york" "SaaS"',
    'site:linkedin.com "co-founder" "NYC" "software" -jobs -learning',
]

Key rules:

  • Always use from ddgs import DDGS (never duckduckgo_search)
  • Use site:linkedin.com NOT site:linkedin.com/in — DDG doesn't support path-level site: queries
  • Exclude noise: -jobs -learning -courses -hiring -pulse
  • Sleep 2s between queries to avoid rate limits
  • Deduplicate by URL across all queries

3. Execute Searches

Use scripts/ddg_search.py for individual queries, or inline for batch:

from ddgs import DDGS
import time

seen = set()
results = []
for q in queries:
    with DDGS() as ddgs:
        for r in ddgs.text(q, max_results=15):
            if r['href'] not in seen:
                seen.add(r['href'])
                results.append(r)
    time.sleep(2)

4. Filter to Profiles

  • LinkedIn profiles: /in/ in URL
  • Crunchbase people: /person/ in URL
  • Company pages: /organization/ or /products/ in URL

5. Enrich from Snippets

Extract from DDG snippets (no extra requests needed):

  • Name: from title (before first -)
  • Company: from title or snippet
  • Title: from snippet (Founder, CEO, Co-Founder, etc.)
  • Location: from snippet
  • Details: funding, company description from snippet

6. Output Structured List

Present as a clean table:

| # | Name | Title | Company | Location | Profile URL |

Multi-Step Flows

When the ask requires finding companies first, then people:

Step 1 — Find companies:

site:crunchbase.com/organization "{industry}" "{city}"
site:g2.com/products "{category}"
site:clutch.co "{service}" "{city}"

Step 2 — For each company, find people:

site:linkedin.com "{company_name}" "founder" OR "CEO"
site:crunchbase.com/person "{company_name}"

Example: "Find Shopify partners in LA, then their founders"

  1. site:apps.shopify.com "{category}" or site:shopify.com/partners "los angeles"
  2. Extract company names from results
  3. site:linkedin.com "{company}" "founder" "los angeles" for each

Edge Cases

  • Few results? Broaden: remove location, use synonyms, try more sources
  • Too noisy? Add exclusions: -jobs -hiring -agency -freelancer
  • Non-English markets? Set region in DDG: region='de-de', region='es-es'
  • Rate limited? Increase sleep to 3-5s, reduce max_results per query

What This Skill Does NOT Do

  • Find email addresses (pair with an email-finder skill)
  • Verify data accuracy (DDG snippets are best-effort)
  • Access gated LinkedIn data (only public snippet info)

Contract & API

Machine endpoints, protocol fit, contract coverage, invocation examples, and guardrails for agent-to-agent use.

MissingGITHUB OPENCLEW

Endpoints

Dossier APISnapshot APIContract APITrust API

Contract coverage

Status

missing

Auth

None

Streaming

No

Data region

Unspecified

Protocol support

OpenClaw: self-declared

Requires: none

Forbidden: none

Guardrails

Operational confidence: low

No positive guardrails captured.
Invocation examples
curl -s "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/snapshot"
curl -s "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/contract"
curl -s "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/trust"

Reliability & Benchmarks

Trust and runtime signals, benchmark suites, failure patterns, and practical risk constraints.

Missingruntime-metrics

Trust signals

Handshake

UNKNOWN

Confidence

unknown

Attempts 30d

unknown

Fallback rate

unknown

Runtime metrics

Observed P50

unknown

Observed P95

unknown

Rate limit

unknown

Estimated cost

unknown

Do not use if

Contract metadata is missing or unavailable for deterministic execution.
No benchmark suites or observed failure patterns are available.

Media & Demo

Every public screenshot, visual asset, demo link, and owner-provided destination tied to this agent.

Missingno-media
No screenshots, media assets, or demo links are available.

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Neighboring agents from the same protocol and source ecosystem for comparison and shortlist building.

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Machine Appendix

Contract JSON

{
  "contractStatus": "missing",
  "authModes": [],
  "requires": [],
  "forbidden": [],
  "supportsMcp": false,
  "supportsA2a": false,
  "supportsStreaming": false,
  "inputSchemaRef": null,
  "outputSchemaRef": null,
  "dataRegion": null,
  "contractUpdatedAt": null,
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Invocation Guide

{
  "preferredApi": {
    "snapshotUrl": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/snapshot",
    "contractUrl": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/contract",
    "trustUrl": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/trust"
  },
  "curlExamples": [
    "curl -s \"https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/snapshot\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/contract\"",
    "curl -s \"https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/trust\""
  ],
  "jsonRequestTemplate": {
    "query": "summarize this repo",
    "constraints": {
      "maxLatencyMs": 2000,
      "protocolPreference": [
        "OPENCLEW"
      ]
    }
  },
  "jsonResponseTemplate": {
    "ok": true,
    "result": {
      "summary": "...",
      "confidence": 0.9
    },
    "meta": {
      "source": "GITHUB_OPENCLEW",
      "generatedAt": "2026-10-09T10:06:58.701Z"
    }
  },
  "retryPolicy": {
    "maxAttempts": 3,
    "backoffMs": [
      500,
      1500,
      3500
    ],
    "retryableConditions": [
      "HTTP_429",
      "HTTP_503",
      "NETWORK_TIMEOUT"
    ]
  }
}

Trust JSON

{
  "status": "unavailable",
  "handshakeStatus": "UNKNOWN",
  "verificationFreshnessHours": null,
  "reputationScore": null,
  "p95LatencyMs": null,
  "successRate30d": null,
  "fallbackRate": null,
  "attempts30d": null,
  "trustUpdatedAt": null,
  "trustConfidence": "unknown",
  "sourceUpdatedAt": null,
  "freshnessSeconds": null
}

Capability Matrix

{
  "rows": [
    {
      "key": "OPENCLEW",
      "type": "protocol",
      "support": "unknown",
      "confidenceSource": "profile",
      "notes": "Listed on profile"
    },
    {
      "key": "path",
      "type": "capability",
      "support": "supported",
      "confidenceSource": "profile",
      "notes": "Declared in agent profile metadata"
    }
  ],
  "flattenedTokens": "protocol:OPENCLEW|unknown|profile capability:path|supported|profile"
}

Facts JSON

[
  {
    "factKey": "docs_crawl",
    "category": "integration",
    "label": "Crawlable docs",
    "value": "6 indexed pages on the official domain",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  },
  {
    "factKey": "vendor",
    "category": "vendor",
    "label": "Vendor",
    "value": "Hanseflats",
    "href": "https://github.com/Hanseflats/list-building-skill",
    "sourceUrl": "https://github.com/Hanseflats/list-building-skill",
    "sourceType": "profile",
    "confidence": "medium",
    "observedAt": "2026-02-25T01:47:35.153Z",
    "isPublic": true
  },
  {
    "factKey": "protocols",
    "category": "compatibility",
    "label": "Protocol compatibility",
    "value": "OpenClaw",
    "href": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/contract",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/contract",
    "sourceType": "contract",
    "confidence": "medium",
    "observedAt": "2026-02-25T01:47:35.153Z",
    "isPublic": true
  },
  {
    "factKey": "handshake_status",
    "category": "security",
    "label": "Handshake status",
    "value": "UNKNOWN",
    "href": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/trust",
    "sourceUrl": "https://www.xpersona.co/api/v1/agents/hanseflats-list-building-skill/trust",
    "sourceType": "trust",
    "confidence": "medium",
    "observedAt": null,
    "isPublic": true
  }
]

Change Events JSON

[
  {
    "eventType": "docs_update",
    "title": "Docs refreshed: Sign in to GitHub · GitHub",
    "description": "Fresh crawlable documentation was indexed for the official domain.",
    "href": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceUrl": "https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar",
    "sourceType": "search_document",
    "confidence": "medium",
    "observedAt": "2026-04-15T05:03:46.393Z",
    "isPublic": true
  }
]

Sponsored

Ads related to list-building and adjacent AI workflows.