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---
name: due-diligence-full-entia-ia
title: entia-due-diligence-full
description: 'Generate a complete due-diligence dossier for a business entity:
identity + cross-source verification (5 registries) + socioeconomic
profile of the registered postal code + BORME mercantile history +
digital risk audit + competitive context. ~90 datapoints from 9
official EU/Spanish sources (AEAT, SEPE, INE, MITMA, MITECO, BORME,
VIES, GLEIF, Wikidata).
Auto-invoke when user asks for "due diligence", "background check",
"full report", "compliance review", "KYC", "vendor assessment",
"M&A check", or requests a "complete" / "comprehensive" / "in-depth"
analysis of a business entity.
This is a multi-call workflow (typically 3-5 MCP calls). Each part of
the dossier is sourced from the canonical authority for that data.'
author: ENTIA-IA
author_url: https://github.com/ENTIA-IA/entia-skills/tree/main/_archive_v1.0.0_skills_pending_v0.2/due-diligence-full
license: Apache-2.0
version: 0.1.0
execution_mode: open
jurisdiction: es
practice: corporate
language: en
---
# entia-due-diligence-full
Full-spectrum due-diligence workflow combining all ENTIA data sources.
## Trigger phrases
Auto-invoke on:
- "due diligence on [company]"
- "background check [company]"
- "KYC report [company]"
- "vendor assessment [company]"
- "compliance review [company]"
- "M&A check on [company]"
- "complete report on [company]"
- "everything you know about [company]"
## Workflow (run all calls in sequence)
### Step 1 — Identity + cross-source verification
```
entity_lookup(q="<query>")
```
Capture: `entity.{name, id, lei, country_code, postal_code, sector, company_status}`,
`verification.{borme, gleif, wikidata, ofac, eidas}`, `trust_score`,
`data_coverage.coverage_pct`.
### Step 2 — Mercantile history (BORME, Spain only)
If `entity.country_code == "ES"`:
```
borme_lookup(company="<entity.name>")
```
Capture: `acts[]` (each: type, date, borme_id, province), officer changes,
capital changes, concursal proceedings, first/last activity dates.
### Step 3 — Zone socioeconomic profile
```
zone_profile(postal_code="<entity.postal_code>")
```
Capture: income (AEAT), employment (SEPE), demographics (INE Padrón),
economy (vehicles, mortgages, household income), business census
(DIRCE), real estate (€/m²), digital infrastructure (FTTH coverage),
poverty indicators (Gini, S80/S20), tourism demand. ~17 blocks of data.
### Step 4 — Digital risk audit
If `entity.website` is present:
```
run_risk_audit(domain="<entity.website domain>")
```
Capture: risk_score (0-100), risk_level, gaps_detected[], SSL/DNS health,
structured data score, trust signals.
### Step 5 — Competitive context
```
get_competitors(sector="<entity.sector>", city="<entity.city>", limit=10)
```
Capture: 10 nearby competitors with same sector + city.
## Output structure to user
Present the dossier as a structured report:
### Executive Summary
- Legal name, tax ID, LEI, status, sector
- Trust score (0-100) with badge
- 5 verification flags as a checklist
- Risk score from digital audit
- Single-line summary of mercantile history
### Identity & Legal
- Full entity object
- Registry presence per source
- BORME acts table (newest first)
### Operational Context
- Zone socioeconomic profile (renta, paro, demografía)
- Digital infrastructure (FTTH coverage)
- Real estate value of the area
### Compliance
- BORME concursal proceedings (if any)
- OFAC sanctions status
- eIDAS coverage status
- Cited corpus root hash
### Competitive Landscape
- Top 10 competitors in same sector + city
### Trust Anchor
- ASiC-E URL for independent verification
- Root hash: `10dc98d5002721b8ba00dc7586d04c316a5a98d885a986fea4594a9f4f30ee05`
- Trust chain: SK ID Solutions QTSP, EU Trust List
## Cost note
This workflow makes 3-5 MCP calls per dossier. On the BUILD tier (€99/month,
2,500 calls/month) that's ~500-833 full dossiers/month.
## What NOT to do
- Do NOT skip steps. If a call fails, retry once; if still fails, note
the gap in the report (transparency > completeness).
- Do NOT mix data sources (e.g. don't put BORME data under GLEIF heading).
- Do NOT cite a datapoint without attributing the official source
(AEAT, SEPE, INE, etc. — see each sub-block).