git-subtree-dir: fiscal git-subtree-mainline:d95165fc8fgit-subtree-split:102ba84500
3.2 KiB
Autonomous Fiscal Completion V1 Design
Goal
Reduce deterministic fiscal gaps across the five explicitly allowlisted local Firebird databases without calling an AI provider, answering human decisions, or treating a populated ERP field as mandatory by default.
Safety Boundary
All discovery and evidence extraction is read-only. Deterministic writes are
permitted only through the existing guarded executor, only for exact allowlisted
paths and proven write targets. A write requires provenance, CHANGE_REQUIRED,
write_eligible=true, path/company/schema/type guards, compare-before-write,
exact rowcount, post-write equality, and a no-unplanned-columns audit. If any
guard fails, the result remains pending. AI flags remain
AI_WRITE_ALLOWED=false and FIREBIRD_AI_WRITES=0.
Workstreams
1. Requiredness and completeness
Create a versioned requiredness matrix for the 23 existing fiscal contracts.
Rules are keyed by company regime/UF and product/operation facts, and produce
one of REQUIRED, CONDITIONAL, OPTIONAL_REFERENCE, NOT_APPLICABLE, or
ERP_NOT_USED. Implement FiscalCompletenessEvaluator to return a status per
field and aggregate product metrics without requiring empty NOT_APPLICABLE
fields to be filled.
2. Inbound evidence
Perform schema discovery across all five databases without assuming table names. Identify headers, items, suppliers, keys, XML/BLOB/text evidence, and relationships. Produce a sanitized evidence map and read-only analysis counts. Supplier observations remain observational until conservative deterministic rules prove they are reusable.
3. Deterministic resolution
Build provenance-aware evidence aggregation for origin, product role, ST/CEST,
and dynamic CFOP entry scope. Use supplier/document agreement metrics rather
than majority alone. Keep conflicts, missing evidence, company/group/product
questions, and ST_WITHHELD uncertainty pending. Reuse only compatible global
KB facts; tenant-specific policy fields are never copied cross-tenant.
Run dry-run and completeness metrics for all five databases. Execute only eligible deterministic writes, then reprocess and require zero second-pass writes. Preserve all current NCM conflicts.
4. Providers and AI controls
Document external product-data provider candidates without purchasing or querying them. Add an abstract provider contract and permanent-cache schema for GTIN/provider/version/hash/normalized data. Add persistent central AI usage ledger and atomic pre-call limits for run, daily, monthly, requests, and new products. Prove idempotent cache behavior with offline tests; no provider or AI network call is made.
Artifacts
The implementation must produce the requiredness matrix, inbound evidence map,
provider evaluation, consolidated JSON/Markdown autonomy reports, and updated
AI_PROJECT_STATE.md. Artifacts must report measured values and explicit
unknowns rather than inferred fiscal answers.
Verification
Each workstream adds focused tests. The final gate runs the complete tests and
central/tests suites, git diff --check, read-only invariant checks, dry-run
and second-pass metrics, and confirms no external AI calls, no non-allowlisted
database access, and no semantic Firebird writes.