NG Lawyer DB Build (Step 1)
What this skill does
This is Step 1 of Fei Gao’s “Nigeria Lawyer Network” workflow:
1) Build a Lawyer Database (this skill)
2) Send outreach emails and score by response (separate skill)
3) Sort & export for fast lookup (separate skill)
The objective is to create a database that allows fast matching by:
City → Practice → Sub-specialty → Regulator → Firm size → Position → Score → Contact.
This skill focuses on data collection + structured classification with evidence links.
Inputs
- city:
Lagos | Abuja - practice:
Construction | RealEstate | Labour | Tax | Criminal | IP - n_per_segment: integer (target 3)
Output files
- lawyer_db_ng.xlsx (main database)
- sources.jsonl (evidence per record: url + snippet + timestamp)
Database schema (fixed column order)
The Excel must contain columns in this exact order:
- Lawyer_UID
- Country
- City
- Practice
- Sub_Practice
- Regulator_Tag
- Firm_Name
- Firm_Size
- Position
- Lawyer_Name
- Email
- Phone
- LinkedIn
- Website
- Evidence_URL
- Score_Total (blank in Step 1)
- Score_ResponseSpeed (blank)
- Score_Detail (blank)
- Score_Pricing (blank)
- Score_Cooperation (blank)
- Risk_Flag (blank)
- NeedFollowUp (0/1)
- ChannelCostRisk (Low/Medium/High)
- Last_Updated
Non-negotiable rules (to avoid future scoring chaos)
1) Unique key (Lawyer_UID)
All later scoring MUST be written back by Lawyer_UID, never by name.
Format:
LAW-NG-{CITYCODE}-{PRACTICECODE}-{NNNN}- CityCode: Lagos=LAG, Abuja=ABJ
- PracticeCode: Construction=CON, RealEstate=REA, Labour=LAB, Tax=TAX, Criminal=CRI, IP=IPR
Example:
2) Email policy (anti-channel-cost)
- Email must be explicitly published on the evidence page (law firm bio page, author page, or official profile).
- NO guessing (e.g., firstname.lastname@firm.com is not allowed unless shown).
- If only a general firm email exists (info@ / contact@), it may be used but set:
ChannelCostRisk=HighNeedFollowUp=1
3) Evidence chain
Each row must store Evidence_URL.
The skill also writes sources.jsonl with:
- Lawyer_UID
- Evidence_URL
- Evidence_Snippet (<= 300 chars)
- Captured_At
4) Firm_Size classification (fee proxy)
Firm_Size affects pricing expectation. Classify using evidence:
- Top:
- The firm is ranked in Chambers or Legal 500 in Nigeria for the relevant practice; OR
- Firm lawyer count > 50 (evidence required)
- Mid: lawyer count 15–50
- Small: lawyer count 2–14
- Solo: sole practitioner / independent (count=1)
- Unknown: insufficient evidence → set NeedFollowUp=1
5) Position mapping (fee proxy)
Normalize to:
- Partner / Counsel / SeniorAssociate / Associate / Junior / Independent / Unknown
Mapping hints:
- Partner: Managing Partner, Senior Partner, Partner
- Counsel: Counsel, Of Counsel
- SeniorAssociate: Senior Associate, Associate (Senior)
- Associate: Associate, Solicitor
- Junior: Junior Associate, Trainee
- Independent: Sole Practitioner, Principal, Independent Legal Practitioner
Regulator_Tag (only with evidence)
Allowed values:
- CAC, NIPC, FIRS, StateIRS, NAFDAC, Immigration, MinistryOfMines, IPRegistry, EFCC, Police, Court
Rule:
- Tag only when evidence mentions regulator or shows relevant matters.
- If not evidenced, leave blank; outreach email will ask the lawyer to self-report regulators handled.
Data collection strategy (recommended sources)
Priority order:
1) Chambers / Legal 500 ranked firms for Nigeria practice (Top candidates)
2) Official law firm team pages (bio pages with emails)
3) Author pages on firm sites / Lexology / IFLR (when email is shown)
4) Boutique firm sites for Small/Solo
Segmentation target
For each (Firm_Size x Position) segment, collect n_per_segment candidates with verified emails where possible.
Recommended priority within Top firms:
- Counsel / SeniorAssociate / Associate (often more willing for flexible cooperation)
Example run (MVP)
City: Lagos
Practice: Construction
n_per_segment: 3
Goal: produce a usable initial database for Lagos Construction to validate:
- Firm_Size classification is correct
- Position mapping is correct
- Emails are evidence-backed
- Column order is stable