Regulatory Templates - Gate 1: Placeholder Mapping (Post Gate 0)

Overview

UPDATED: Gate 1 now maps placeholders from Gate 0 template to data sources. NO structure creation, NO logic addition.

Parent skill: regulatory-templates

Prerequisites:

Context from regulatory-templates-setup
Template base from regulatory-templates-setup

Output: Mapping of placeholders to backend data sources

Foundational Principle

Field mapping errors compound through Gates 2-3 and into production.

Gate 1 is the foundation of regulatory template accuracy:

snake_case conversion: Python/Django ecosystem standard (PEP 8) - mixed conventions cause maintenance nightmares
Data source prefixes: BACEN audits require data lineage traceability - "where did this value come from?"
Interactive validation: No dictionary = no ground truth - user approval prevents assumption errors
Confidence thresholds: Quality gates prevent low-confidence mappings from reaching production
Dictionary checks: Consistency across team, audit trail for regulatory reviews

Every "shortcut" in Gate 1 multiplies through downstream gates:

Skip snake_case → Gate 3 templates have mixed conventions → maintenance debt
Skip prefixes → Gate 2 cannot trace data sources → debugging nightmares
Auto-approve mappings → Gate 2 validates wrong assumptions → compliance violations
Skip optional fields → Gate 1 fails confidence threshold → rework loops
Lower thresholds → Low-confidence fields reach Gate 3 → production errors

Technical correctness in Gate 1 = foundation for compliance in production.

When to Use

Called by: regulatory-templates skill after Gate 0 template structure copy

Purpose: Map each placeholder to its data source - structure already defined in Gate 0

NO EXCEPTIONS - Technical Requirements Are Mandatory

Gate 1 field mapping requirements have ZERO exceptions. Every requirement exists to prevent specific failure modes.

Common Pressures You Must Resist

Pressure	Your Thought	Reality
Speed	"camelCase works, skip conversion"	PEP 8 violation creates maintenance debt. 30 min now vs 75+ min debugging later
Simplicity	"Prefix is verbose, omit it"	BACEN audits require data lineage. Implicit resolution = debugging nightmares
Efficiency	"AUTO-approve obvious mappings"	No dictionary = no ground truth. "Obvious" assumptions cause compliance violations
Pragmatism	"Skip optional fields"	Confidence calculated across ALL fields. 64% coverage = FAIL
Authority	"75% confidence is enough"	Threshold erosion: 75% → 70% → 60%. LOW confidence fields = high-risk mappings
Experience	"I memorized these, skip dictionary"	Memory is fallible. 1-min check prevents 20-40 min error correction

Technical Requirements (Non-Negotiable)

snake_case Conversion:

✅ REQUIRED: Convert ALL field names to snake_case
❌ FORBIDDEN: Use camelCase, PascalCase, or mixed conventions
Why: Python/Django PEP 8 standard, grep-able patterns, maintenance

Data Source Prefixes:

✅ REQUIRED: {{ midaz_onboarding.organization.0.legal_document }}
❌ FORBIDDEN: {{ organization.legal_document }}
Why: Data lineage traceability, multi-source disambiguation, audit compliance

Interactive Validation:

✅ REQUIRED: AskUserQuestion for EACH field mapping
❌ FORBIDDEN: Auto-approve HIGH confidence fields
Why: No dictionary = no ground truth, user provides domain knowledge

Confidence Threshold:

✅ REQUIRED: Overall confidence ≥ 80%
❌ FORBIDDEN: Lower threshold or skip fields
Why: Quality gate for Gate 2/3, prevents low-confidence mappings in production

Dictionary Check:

✅ REQUIRED: Check ~/.claude/docs/regulatory/dictionaries/ first
❌ FORBIDDEN: Skip check and use memory
Why: Consistency, audit trail, error prevention

The Bottom Line

Shortcuts in field mapping = errors in production regulatory submissions.

Gate 1 creates the foundation for Gates 2-3. Technical correctness here prevents compliance violations downstream.

If you're tempted to skip ANY requirement, ask yourself: Am I willing to debug production BACEN submission failures caused by this shortcut?

Anti-Rationalization Table

CRITICAL: Prevent yourself from making these autonomous decisions.

Rationalization	Why It's WRONG	Required Action
"camelCase works fine in Django"	PEP 8 violation, maintenance debt, inconsistent conventions	Convert ALL to snake_case
"Prefix is verbose and ugly"	Audit trail required, multi-source disambiguation critical	Prefix ALL fields with data source
"HIGH confidence = obvious, no approval needed"	No dictionary = no ground truth, assumptions fail	Ask approval for EACH field
"Optional fields don't affect compliance"	Confidence calculated across ALL fields, 64% = FAIL	Map ALL fields (mandatory + optional)
"75% is close to 80%, good enough"	Threshold erosion, LOW confidence = high risk	Research to ≥80% or FAIL
"I know these mappings by heart"	Memory fallible, experience creates overconfidence	Check dictionary first
"Everyone knows where organization comes from"	Implicit tribal knowledge, new team members lost	Explicit prefix beats implicit
"User approval wastes their time"	User provides domain knowledge we lack	Interactive validation MANDATORY
"Conversion is unnecessary busywork"	Dismissing requirements without understanding cost	Technical correctness prevents debt
"This is simple, process is overkill"	Simple tasks accumulate into complex problems	Follow workflow completely
"Dictionary probably doesn't exist anyway"	1-minute check vs 20-minute correction	ALWAYS check dictionary path
"MCP API will have the field, skip check"	API schema changes, fields deprecate	VERIFY field exists before mapping

If You Find Yourself Making These Excuses

STOP. You are rationalizing.

The requirements exist to prevent these exact thoughts from causing errors. If a requirement seems "unnecessary," that's evidence it's working - preventing shortcuts that seem reasonable but create risk.

CRITICAL CHANGE

❌ OLD Gate 1 (Over-engineering)

Created complex field mappings
Added transformation logic
Built nested structures
Result: 90+ line templates

✅ NEW Gate 1 (Simple)

Takes template from Gate 0
Maps placeholders to single data source
NO structural changes
Result: <20 line templates

🔴 CRITICAL: NAMING CONVENTION - SNAKE_CASE STANDARD

ALL field names MUST be converted to snake_case:

✅ If API returns legalDocument → convert to legal_document
✅ If API returns taxId → convert to tax_id
✅ If API returns openingDate → convert to opening_date
✅ If API returns naturalPerson → convert to natural_person
✅ If API returns tax_id → keep as tax_id (already snake_case)

ALWAYS convert camelCase, PascalCase, or any other convention to snake_case.

🔴 CRITICAL: DATA SOURCES - ALWAYS USE CORRECT DOMAIN PREFIX

REFERENCE: See /docs/regulatory/DATA_SOURCES.md for complete documentation.

Available Data Sources (Reporter Platform):

Data Source	Descrição	Entidades Principais
`midaz_onboarding`	Dados cadastrais	organization, account
`midaz_transaction`	Dados transacionais	operation_route, balance, operation
`midaz_onboarding_metadata`	Metadados cadastro	custom fields
`midaz_transaction_metadata`	Metadados transações	custom fields

Field Path Format: {data_source}.{entity}.{index?}.{field}

Examples: {{ midaz_onboarding.organization.0.legal_document }} | {{ midaz_transaction.operation_route.code }} | {{ midaz_transaction.balance.available }}

Common Mappings: CNPJ→organization.0.legal_document, COSIF→operation_route.code, Saldo→balance.available

RULE: Always prefix with data source! ❌ {{ organization.legal_document }} → ✅ {{ midaz_onboarding.organization.0.legal_document }}

Gate 1 Process

PRE-STEP 0: Mandatory Pre-Checks (BEFORE any field mapping)

MANDATORY: Execute these checks before EVERY Gate 1 analysis.

0a. Load DATA_SOURCES.md Read finops-team/docs/regulatory/templates/DATA_SOURCES.md (or .claude/docs/regulatory/templates/DATA_SOURCES.md in project context). This is the canonical reference for all available Reporter fields and data source prefixes. BLOCKER: If file not found → use hierarchy from memory: CRM first for personal/banking, midaz_transaction for accounting, midaz_onboarding for organizational.

0b. Fetch Reporter documentation (source of truth) The official Reporter documentation is the authoritative reference for template syntax and available filters.

URL is provided in context as reporter_docs_url (if configured in Setup)
If reporter_docs_url is available: fetch current documentation before proceeding
If unavailable: use local fallback at finops-team/docs/regulatory/templates/reporter-guide.md
NEVER rely solely on memorized filter list — Reporter may have added or removed filters

0c. Cross-dictionary pattern matching (for templates WITHOUT dictionary) Before MCP discovery, search existing dictionaries in .claude/docs/regulatory/dictionaries/ for patterns:

If field looks like...	Check this first
CNPJ / document number	`midaz_onboarding.organization.0.legal_document`
COSIF code / account code	`midaz_transaction.operation_route.code`
Balance / saldo	`midaz_transaction.balance.available`
Holder name / client name	`crm.holder.name`
Branch / agência	`crm.alias.banking_details.branch`
Account number	`crm.alias.banking_details.account_number`
Date of birth	`crm.holder.natural_person.date_of_birth`
Address	`crm.holder.addresses.primary.*`
GIIN / FATCA	`midaz_onboarding.organization.0.metadata.giin`

This dramatically reduces the number of fields requiring MCP discovery or user input.

STEP 1: Check for Data Dictionary (FROM/TO Mappings)

HIERARCHICAL SEARCH - Dictionary first, Batch Approval second:

Dictionary Path: ~/.claude/docs/regulatory/dictionaries/{category}-{code}.yaml

Step	If Dictionary EXISTS	If Dictionary NOT EXISTS
1	Load YAML, use field_mappings	Run Pre-Step 0c (pattern matching) first
2	Apply transformations	Query MCP: `mcp__apidog_midaz__read_project_oas()` for remaining fields
3	Use existing mappings	Group fields by confidence → Batch Approval (see below)
4	Return	Auto-save dictionary (see Auto-Save section below)
5	—	Update registry.yaml with new entry

Dictionary contains: field_mappings (FROM→TO), transformations, pitfalls, validation_rules

🔴 CRITICAL: VALIDATION FOR TEMPLATES WITHOUT DICTIONARY

Data Dictionaries Location

Dicionários de dados disponíveis em: ~/.claude/docs/regulatory/dictionaries/

Consulte os dicionários existentes antes de iniciar o mapeamento de campos.

Batch Approval Process (supersedes field-by-field AskUserQuestion for HIGH/MEDIUM)

Reconciliation note: This section supersedes any earlier instruction in this document that requires AskUserQuestion per-field for HIGH or MEDIUM confidence fields. The batch flow below is the authoritative approval process for templates without dictionary. Per-field AskUserQuestion applies ONLY to LOW confidence fields (< 60%). Each field is still presented and user-approved — just in groups rather than one at a time. This reduces interaction from 40–100 min to 10–15 min without removing user control.

After MCP discovery and pattern matching, group fields by confidence level:

Confidence	Threshold	Approval method	Est. time
HIGH	≥ 90%	Present ALL at once → single YES/NO	~1 min
MEDIUM	60–89%	Groups of 5 → review each group	~5–10 min
LOW	< 60%	Field-by-field (genuinely uncertain)	~1–2 min/field

Example HIGH confidence batch presentation:

Aprovação em lote — campos HIGH confidence (23 campos):

✓ CNPJ Base     → midaz_onboarding.organization.0.legal_document | slice:':8'   (95%)
✓ Código COSIF  → midaz_transaction.operation_route.code                         (92%)
✓ Saldo Disp.   → midaz_transaction.balance.available | floatformat:2            (91%)
✓ Nome titular  → crm.holder.name                                                 (94%)
[... demais campos HIGH ...]

Aprovar TODOS os 23 campos acima? [Sim / Não — revisar um a um]

This replaces the old O(n) question flow. Estimated total: 10–15 min vs 40–100+ min.

Auto-Save Dictionary (MANDATORY after user approval)

After all field mappings are approved, execute these steps before returning Gate 1 result:

STEP A: Generate dictionary YAML Create a complete dictionary file following the format of existing dictionaries (check .claude/docs/regulatory/dictionaries/ for format reference).

STEP B: Save dictionary file

Save to the canonical registry path (so the registry entry and Setup discovery will find it):

Path: finops-team/docs/regulatory/templates/{AUTHORITY}/{CATEGORY}/{CODE}/dictionary.yaml
Example: finops-team/docs/regulatory/templates/BACEN/CADOC/4030/dictionary.yaml
         finops-team/docs/regulatory/templates/RFB/EFINANCEIRA/evtMovOpFin/dictionary.yaml

This path must match the reference_files.dictionary value added to registry.yaml in STEP C.

STEP C: Update registry.yaml Append the new template entry to finops-team/docs/regulatory/templates/registry.yaml:

{AUTHORITY}_{CATEGORY}_{CODE}:
  display_name: "{Template Full Name}"
  authority: "{BACEN|RFB|other}"
  category: "{CADOC|EFINANCEIRA|DIMP|APIX|other}"
  code: "{code}"
  format: "{XML|TXT|HTML}"
  frequency: "{monthly|semestral|annual|per_period}"
  status: active
  description: "{brief description}"
  has_dictionary: true
  validation_mode: automatic
  reference_files:
    dictionary: "{authority}/{category}/{code}/dictionary.yaml"
  fields_count: {N}
  mandatory_fields: {M}

STEP D: Confirm to user

"✅ Dicionário salvo em .claude/docs/regulatory/dictionaries/{filename}.yaml. Na próxima execução deste template, o workflow será automático (~5 min em vez de ~15 min)."

BLOCKER: If save fails (permissions, path error) → STOP. Cannot proceed to Gate 2 until dictionary is persisted. Report exact error and path.

Interactive Validation Process (field-by-field, only for LOW confidence fields)

Step	Action	Details
A	Discover Fields	Read regulatory spec (XSD/PDF/URL) → Extract ALL required fields + types + formats
B	Pattern Matching	Apply Pre-Step 0c patterns before MCP calls
C	Query API Schemas	`mcp__apidog_midaz__read_project_oas()` for fields not resolved by pattern matching
D	Batch Approval	Group HIGH/MEDIUM/LOW → present by group (see Batch Approval above)
E	Individual Validation	For LOW confidence only: AskUserQuestion with top 3-4 suggestions + "Skip" + "Other"
F	Validate Transformations	If field needs transform: confirm filter (e.g., `slice:':8'`, `floatformat:2`)
G	Auto-Save Dictionary	Execute Auto-Save steps A–D above (MANDATORY)

AskUserQuestion Implementation for Field Mapping

CRITICAL: Use AskUserQuestion tool with these patterns:

Pattern	Question Format	Options
Field Source	`Map '${field.name}' (${type}, ${required})?`	Top 3 suggestions (with confidence %) + "Skip for now" + "Other" (auto)
Transformation	`Transformation for '${field.name}'?`	Suggested filters (with examples) + "No transformation" + "Other" (auto)
Batch Approval	`Approve mapping for '${name}'? Suggested: ${path}, Confidence: ${%}`	"Approve ✓" / "Reject ✗" (max 4 questions per batch)

Note: "Other" option automatically added by AskUserQuestion for custom input.

Complete Interactive Validation Flow

Process: Read spec → Query MCP schemas → For EACH field: AskUserQuestion → Process response → Track approved/skipped

Response Type	Action
"Skip"	Add to skippedFields (resolve in Gate 2)
Custom input ("Other")	Add with `approved_by: "user_custom_input"`, confidence: 100
Suggested option	If needs transformation: ask for filter (slice, floatformat, etc.) → Add with `approved_by: "user_selection"`

Output: { approvedMappings: [...], skippedFields: [...] }

Validation Rules for User Input

Valid path patterns for custom input:

Source	Pattern	Example
`midaz_onboarding`	`midaz_onboarding.(organization\|account).N.field`	`midaz_onboarding.organization.0.legal_document`
`midaz_transaction`	`midaz_transaction.(operation_route\|balance\|operation).field`	`midaz_transaction.balance.available`
`crm`	`crm.(holder\|alias).field`	`crm.holder.document`
`metadata`	`(midaz\|crm).entity.metadata.field`	`midaz.account.metadata.branch`

Validation: If path doesn't match patterns → warn user but allow (may be valid custom path).

NAMING CONVENTION IN FIELD DISCOVERY

CRITICAL: ALWAYS CONVERT TO SNAKE_CASE!

API Returns	Map As	✅/❌
`legalDocument`	`organization.legal_document`	✅
`taxId` / `TaxID`	`organization.tax_id`	✅
`openingDate`	`organization.opening_date`	✅
`legalDocument`	`organization.legalDocument`	❌ NEVER

Search patterns help FIND fields. Once found, CONVERT TO SNAKE_CASE!

Hierarchical Search Strategy

CRITICAL: Convert ALL discovered fields to snake_case!

Step	Action	Priority Paths
1	Query MCP schemas	`mcp__apidog_midaz__read_project_oas()`
2	Search CRM first	holder.document, holder.name, holder.type, holder.addresses., holder.contact., holder.naturalPerson., holder.legalPerson., alias.bankingDetails., alias.metadata.
3	Search Midaz second	account.name, account.alias, account.metadata., account.status, transaction.metadata., balance.amount, organization.legalDocument
4	Check metadata	crm.holder/alias.metadata., midaz.account/transaction.metadata.
5	Mark as uncertain	If not found → document searched locations + suggest closest matches + indicate confidence

Confidence Scoring System

Level	Score	Criteria
HIGH (90-100%)	Base(30) + Name(25) + System(25) + Type(20) + Validation(20)	Exact name match, type matches, primary system, validation passes, simple/no transform
MEDIUM (60-89%)	Base(30) + partial matches	Partial name or pattern match, compatible type needs transform, secondary system, some uncertainty
LOW (30-59%)	Base(30) only	Synonym/fuzzy match, significant transform, metadata only, cannot validate

Formula: Score = Base(30) + NameMatch(0-25) + SystemMatch(0-25) + TypeMatch(0-20) + ValidationMatch(0-20)

Component	Values
NameMatch	exact=25, partial=15, pattern=5
SystemMatch	primary=25, secondary=15, metadata=5
TypeMatch	exact=20, compatible=10, needs_transform=5
ValidationMatch	validated=20, partial=10, cannot_validate=0

Validation with Examples

Process: Fetch sample → Apply transformation → Validate format

Pattern	Regex
CPF	`/^\d{11}$/`
CNPJ	`/^\d{14}$/`
CNPJ_BASE	`/^\d{8}$/`
DATE_BR	`/^\d{2}\/\d{2}\/\d{4}$/`
DATE_ISO	`/^\d{4}-\d{2}-\d{2}$/`
PHONE_BR	`/^\+?55?\s?$?\d{2}$?\s?\d{4,5}-?\d{4}$/`
CEP	`/^\d{5}-?\d{3}$/`

Example: CNPJ Base: "12345678000190" → slice:':8' → "12345678" → /^\d{8}$/ → ✓ valid (+20 confidence)

Agent Dispatch

Dispatch: Task(subagent_type: "ring:finops-analyzer")

Pre-dispatch: Check dictionary at ~/.claude/docs/regulatory/dictionaries/{category}-{code}.yaml

Mode	Condition	Instructions
Dictionary Mode	File exists	USE dictionary data ONLY. NO MCP calls. Validate mappings.
MCP Discovery Mode	File missing	Query MCP APIs → Suggest mappings → AskUserQuestion for EACH → Create dictionary with APPROVED only

Prompt includes: Template info, dictionary status/content (if exists), snake_case requirement, validation steps, output format

CRITICAL REQUIREMENTS:

✅ DO	❌ NEVER
Check dictionary FIRST	Skip dictionary check
MCP only if no dictionary	Call MCP when dictionary exists
AskUserQuestion for ALL mappings	Auto-approve without asking
Save APPROVED mappings only	Save unapproved guesses
Validate all transformations	Guess field mappings

Report Output: dictionary_status, field_mappings (code, name, required, source, transformation, confidence, validated, examples), validation_summary (total, mapped, coverage%, avg_confidence)

COMPLETION STATUS: COMPLETE, INCOMPLETE, or NEEDS_DISCUSSION

Capture Gate 1 Response

Response structure:

Section	Fields
Template Info	template_name, regulatory_standard, authority, submission_frequency, submission_deadline
Field Counts	total_fields, mandatory_fields, optional_fields
Discovery Summary	crm_fields_available, midaz_fields_available, metadata_fields_used, unmapped_fields
Field Mappings (per field)	field_code, field_name, required, type, format, mappings_found[], selected_mapping, confidence_score, confidence_level, reasoning, transformation, validation_passed, status
Uncertainties (per field)	field_code, field_name, mappings_attempted[], best_match, doubt, suggested_resolution
Confidence Summary	high/medium/low_confidence_fields, overall_confidence
Compliance Risk	LOW/MEDIUM/HIGH (based on confidence levels)
Documentation Used	official_regulatory URL, implementation_reference URL, regulatory_framework

Documentation Sources

Official Regulatory Sources (SOURCE OF TRUTH)

Red Flags - STOP Immediately

If you catch yourself thinking ANY of these, STOP and re-read the NO EXCEPTIONS section:

Skip Patterns

"Skip snake_case conversion for..."
"Omit prefix for obvious fields"
"Use camelCase this time"
"Mixed conventions are fine"
"Dictionary check is ceremony"

Partial Compliance

"Convert only mandatory fields"
"Prefix only ambiguous fields"
"Auto-approve HIGH confidence"
"Map only mandatory fields"
"75% is close enough to 80%"

Experience-Based Shortcuts

"I memorized these mappings"
"I know where this comes from"
"We've done this 50 times"
"The pattern is obvious"
"Dictionary won't exist anyway"

Justification Language

"Unnecessary busywork"
"Verbose and ugly"
"Wasting user time"
"Process over outcome"
"Being pragmatic"
"Close enough"
"Everyone knows"

If You See These Red Flags

Acknowledge the rationalization ("I'm trying to skip snake_case")
Read the NO EXCEPTIONS section (understand why it's required)
Read the Rationalization Table (see your exact excuse refuted)
Follow the requirement completely (no modifications)

Technical requirements are not negotiable. Field mapping errors compound through Gates 2-3.

Severity Calibration

MUST classify field mapping issues using these severity levels:

Severity	Definition	Examples	Gate Impact
CRITICAL	BLOCKS Gate 1 completion OR creates compliance risk	- Mandatory field has NO valid source- Dictionary check skipped- MCP discovery not performed- snake_case conversion skipped	HARD BLOCK - Cannot proceed to Gate 2
HIGH	REQUIRES resolution before Gate 2	- Mandatory field confidence < 60%- Data source prefix missing- Transformation untested- User approval skipped	MUST resolve before proceeding
MEDIUM	SHOULD fix to improve template quality	- Optional field confidence 60-80%- camelCase partially converted- Some fields missing prefix- Interactive validation partial	SHOULD resolve - document if deferred
LOW	Minor improvements possible	- Documentation reference incomplete- Confidence 80-90% (could be higher)- Additional validation possible	OPTIONAL - note in report

Classification Rules:

CRITICAL = ANY of:

Mandatory regulatory field has NO valid source mapping
Dictionary path not checked before MCP calls
snake_case conversion not applied
Data source prefix (midaz_onboarding, midaz_transaction) missing
Interactive validation skipped for templates without dictionary

HIGH = ANY of:

Field mapping confidence < 60% for mandatory fields
Transformation rule needs validation with test data
Multiple possible sources for same regulatory field (ambiguous)
User approval not obtained for uncertain mappings

Cannot Be Overridden

NON-NEGOTIABLE requirements (no exceptions, no user override):

Requirement	Why NON-NEGOTIABLE	Verification
snake_case Conversion	PEP 8 standard, maintenance, grep-ability	ALL fields use snake_case
Data Source Prefix	Audit trail, multi-source disambiguation	ALL fields have midaz_* prefix
Dictionary Check First	Determines validation mode (auto vs 40-min interactive)	Dictionary path checked
Interactive Validation	User provides domain knowledge AI lacks	AskUserQuestion for EACH field
≥80% Confidence Threshold	Quality gate for Gate 2/3	overall_confidence >= 80%

User CANNOT:

Skip snake_case ("camelCase works" = NO)
Omit prefixes ("obvious source" = NO)
Auto-approve HIGH confidence ("no need to ask" = NO)
Map mandatory only ("skip optional" = NO)
Lower threshold ("75% is close" = NO)

Pass/Fail Criteria

PASS Criteria

✅ COMPLETION STATUS: COMPLETE
✅ 0 Critical gaps (unmapped mandatory fields)
✅ Overall confidence score ≥ 80%
✅ All mandatory fields mapped (even if LOW confidence)
✅ < 10% of fields with LOW confidence
✅ Dynamic discovery via MCP executed
✅ Documentation was consulted (both official and implementation)
✅ CRM checked first for banking/personal data

FAIL Criteria

❌ COMPLETION STATUS: INCOMPLETE
❌ Critical gaps exist (mandatory fields unmapped)
❌ Overall confidence score < 60%
❌ > 20% fields with LOW confidence
❌ Documentation not consulted
❌ MCP discovery not performed
❌ Only checked one system (didn't check CRM + Midaz)

State Tracking

Status	Output Fields
PASS	STATUS: PASSED, FIELDS: total/mandatory, UNCERTAINTIES: count, COMPLIANCE_RISK, NEXT: Gate 2, EVIDENCE: docs consulted + all mandatory mapped
FAIL	STATUS: FAILED, CRITICAL_GAPS: count, HIGH_UNCERTAINTIES: count, NEXT: Fix gaps, BLOCKERS: Critical mapping gaps

Critical Validations

Ensure these patterns are followed:

Use EXACT patterns from Lerian documentation
Apply filters like slice, floatformat as shown in docs
Follow tipoRemessa rules: "I" for new/rejected, "S" for approved only
Date formats must match regulatory requirements (YYYY/MM, YYYY-MM-DD)
CNPJ/CPF formatting rules must be exact

Output to Parent Skill

Return to regulatory-templates: { gate1_passed: bool, gate1_context: {...}, uncertainties_count: N, critical_gaps: [], next_action: "proceed_to_gate2" | "fix_gaps_and_retry" }

Common Issues and Solutions

Issue	Solution
Documentation not accessible	Try alternative URLs or cached versions
Field names don't match Midaz	Mark as uncertain for Gate 2 validation
Missing mandatory fields	Mark as Critical gap, must resolve
Format specifications unclear	Consult both Lerian docs and government specs

Dynamic Discovery Example

Finding "Agência" field for CADOC 4010:

Step	Action	Result
1	Pattern search	`["branch", "agency", "agencia", "branch_code"]`
2	Query CRM first	`crm.alias.bankingDetails.branch` ✓ (exact, 95%)
3	Query Midaz fallback	`midaz.account.metadata.branch_code` ⚠ (metadata, 45%)
4	Select highest	`crm.alias.bankingDetails.branch` (HIGH confidence)

Remember

CONVERT TO SNAKE_CASE - All fields must be snake_case (legal_document not legalDocument)
Use MCP for dynamic discovery - Never hardcode field paths
CRM first for banking/personal data - It has the most complete holder info
Official specs are SOURCE OF TRUTH - Regulatory requirements from government
Lerian docs show IMPLEMENTATION - How to create templates in their system
Template-specific knowledge is valuable - Always check for existing sub-skills
Confidence scoring is key - Always calculate and document confidence
Be conservative with mappings - Mark uncertain rather than guess
Capture everything - Gate 2 needs complete context with all attempted mappings
Reference both sources - Note official specs AND implementation examples
Risk assessment based on confidence - Low confidence = higher compliance risk

Important Distinction

⚠️ Regulatory Compliance vs Implementation

WHAT (Requirements) = Official government documentation
HOW (Implementation) = Lerian documentation examples
When validating compliance → Use official specs
When creating templates → Use Lerian patterns
Never confuse implementation examples with regulatory requirements

ring:regulatory-templates-gate1