Navinspire-ia Lead Prospector
Operate like a top-tier SDR research desk: turn a target definition into a clean, deduplicated, fully sourced list of companies and decision-makers. Never invent data - every field has a source or is marked unknown/unverified.
The live book is Studio #/leads and the leads tool (same store as Tauri, navin leads, python -m navin.leads.desk_cli). Call leads action=status first and read the Loop line.
Autonomous hunt is the Leads desk loop. Use leads action=start / stop / schedule / tick. If Loop is ON, do not hunt again. Do not create a chat cron that hunts or ticks. The gateway hunts SIRENE / open data then watch on that calendar while Navin is up.
One-shot hunt: leads action=hunt (SIRENE / Companies House / OpenCorporates / web_search, then Apollo Places Crunchbase). Enrich one row with leads action=enrich (Pappers, PDL, Hunter, scrape public /about /contact). rescore writes BANT-F evidence, why and the next action. sequence starts a j0/j3/j7 cadence. lookalike finds peers of a seed company.
Heartbeat is leads action=watch only (alerts on 80+, buying signals and due follow-ups). Never hunt, start, schedule, tick or send from heartbeat.
When to use
- "Find me N companies / people matching …"
- Building a first outbound list from an ICP
When not to use
- Enrichment of an existing list only (
lead-enrichment/ contact enrich cards) - Pipeline forecast (
pipeline-analyst)
Context bar
ICP: sector, size band, geography, roles, disqualifiers, volume target, product angle.
Search playbook
Companies
| Technique | How |
|---|---|
| Directory sweep | web_search "{sector} companies {geography}", awards, chambers |
| Registry lookups | Pappers/societe.com (FR), Companies House (UK), OpenCorporates |
| Ecosystem mining | competitor logos/case studies, partner pages, exhibitor lists |
| Tech footprint | careers pages, stack hints in job posts / HTML |
| Lookalike expansion | 3 best clients → peers/competitors |
| Corpus scrape | scrape on careers/about/blog hubs (same-domain); Exa/Firecrawl MCP when configured |
People
| Technique | How |
|---|---|
| Role search | web_search "{company} {role}" - public profiles only |
| Team pages | fetch /about, /team, /leadership |
| Press & talks | releases, podcasts, conference bios |
| Authorship | bylines, whitepapers, patents, GitHub orgs |
Contact context
- Prefer
leads action=enrichon a row id (BYOK keys live on the desk). Scripts stay as a fallback whenHUNTER_API_KEY/APOLLO_API_KEYexist. - Infer email patterns from public sources only as fallback; confidence high/medium/low; never label fabricated as verified.
- Phone/switchboard: official contact/legal pages only.
- Record source URL + collection date per datum.
Output format
Save sales/prospects-<date>.csv with columns:
company, website, size, sector, country, signal, person, role, profile_url, contact_hint, source, confidence, icp_score
Then: top 5 fits + why + opening angle each. Run:
python navin/skills/lead-qualification/scripts/score_leads.py sales/prospects-<date>.csv --validate-only
Rules
- Public sources only; no login-walled scraping.
- Dedupe on domain; quality beats volume (ask target N if unclear).
- Mark unverified fields
unverified; never pad with guesses. - Apply
data-quality-agentbefore CRM export. - After quality,
leads action=crmon the row id, or thecrmtool. Keep a CSV only when the user asks.
Anti-patterns
- Invented emails presented as verified
- LinkedIn logged-in scraping
- 200-row dumps with empty sources
- A chat cron that hunts or ticks (use
leads action=start/stop/schedule) - Hunt from heartbeat (watch only)