Schema now accepts the same five levels used elsewhere in the codebase
(minimal/low/medium/high/bypassed) instead of the stale full/restricted/
sandbox triple. Docs and env test updated to match.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Spec for consolidating the three alias tables (benchmark-selector,
auto-model-selection, model-router) into a single SF-extension registry
that reads from @singularity-forge/ai's MODELS and enriches it with
canonical_id, generation, and tier. Shared interface for parallel
Swarm A/B/C work.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
SF's S05/T02 executor moved the doc back to docs/dev/sf-ace-patterns.md
while completing the slice (correctly: that was the task's stated
deliverable location). The doc is parked under docs/dev/drafts/ because
ACE Coder has no active consumer for it; re-park it.
Keep the ADR-019 / ADR-020 cross-references the executor added —
they are real content improvements over the previous version.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Promotes the .draft stub into a fuller 183-line reference covering six
SF patterns (Preferences, PDD, UOK Gates, Notifications, Skills-as-
Contracts, Idempotency) with SF source paths and ACE adoption notes.
Filed under docs/dev/drafts/ with a STATUS: Draft header — no active
consumer yet. SF's own priorities take precedence until ACE Coder
maintainers pull on convergence.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add profile-aware scaffold system so SF does not lay down irrelevant
templates in infra/ops/docs repos.
## What ships
Phase 1 — data model
- scaffold-versioning.js: add 'disabled' to VALID_STATES; readScaffoldManifest
returns profile field; recordScaffoldApply preserves manifest.profile (fixes
roundtrip bug where profile was stripped on every write).
- scaffold-constants.js: PROFILES (app/library/infra/docs/minimal as Set<string>)
and PROFILE_NAMES exports.
Phase 2 — profile-aware drift detection
- scaffold-drift.js: disabled bucket in emptyCounts, resolveActiveProfileSet
integration, profile param on detectScaffoldDrift/migrateLegacyScaffold.
- doc-checker.js: filter to active profile, skip disabled-state files.
Phase 3 — auto-detection on first run
- scaffold-profiles.js: detectRepoProfile() heuristics (nix→infra,
terraform→infra, react→app, node-no-ui→library, docs-only→docs, else→app).
- agentic-docs-scaffold.js: reads profile from manifest, auto-detects on first
run, persists to manifest, filters SCAFFOLD_FILES to active profile.
Phase 4 — migrate command
- commands-scaffold-migrate.js: sf scaffold migrate --profile <name>
Re-enables pending files entering the new profile; stamps state=disabled
(or prunes with --prune) files leaving it; warns on editing/completed files.
- commands/handlers/ops.js, commands/catalog.js: registered and tab-completed.
Phase 5 — custom profiles + PREFERENCES.md frontmatter
- scaffold-profiles.js: readPreferencesProfile(), loadCustomProfileSet()
(~/.sf/profiles/<name>.yaml with extends/add/remove), resolveActiveProfileSet()
implementing full ADR-022 §6 precedence.
- All callers updated to use resolveActiveProfileSet as the single source of truth.
Tests: 28 new tests in adr-022-scaffold-profiles.test.mjs — all passing.
Pre-existing node:test stubs (3 files) unaffected.
ADR: docs/dev/ADR-022-scaffold-profiles.md
Misc: triage TODO.md dump into BACKLOG.md (phases-helpers export error T1,
/todo triage typed-handler gap T1, structured triage tiers T2, sha-track
markdown files T2, cross-repo triage T3). Reset TODO.md to empty template.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- preferences-models.js: replace 6-regex isHeavyModelId() with MODEL_CAPABILITY_TIER
lookup + regex fallback for unknown models; new models in model-router.js
are automatically reflected without touching preferences-models.js
- search-the-web/provider.js: replace ~200-line per-provider waterfall with
PROVIDER_REGISTRY array + firstAvailable()/resolveWithFallback() helpers;
preserves Tavily→Brave→Serper→Exa→Ollama→MiniMax auto-fallback order
- sf-db.js: bump SCHEMA_VERSION 58→60 (v59 now reachable); add
frontmatter_version column to tasks table via v60 migration and CREATE
TABLE definition; wire frontmatter_version into upsertTaskPlanning() SQL
and .run() params
- task-frontmatter.js: add frontmatterVersion:1 to DEFAULT_TASK_FRONTMATTER,
add validation block in validateTaskFrontmatter(), add frontmatterVersion
mapping in taskFrontmatterFromRecord()
- sf-db-migration.test.mjs: update hardcoded version assertion 58→60
- docs/specs/sf-operating-model.md: add Planning Schema section documenting
the 3-table model (milestones/slices/tasks, their PKs, spec tables, and
ID naming conventions)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Implements the 3-table normalization model for milestone, slice, and task entities:
- 9 new tables: {milestone,slice,task}_{specs,evidence} + runtime tables
- milestone_specs: immutable record of intent (vision, goals, risks, proof strategy)
- slice_specs: immutable slice-level intent
- task_specs: immutable task verification criteria
- {entity}_evidence: append-only audit trail with timestamps and phase metadata
- Indices on evidence tables for efficient chronological queries
Key improvements:
- Spec immutability: Write-once specs preserve original intent
- Audit trail: Evidence chain enables data archaeology and decision history
- Query efficiency: Each table contains only relevant columns
- Re-planning clarity: Multiple spec versions can exist for same entity ID
- Forensic capability: Timestamp + phase metadata on evidence rows
Migration:
- Schema version bumped to 32
- Migration runs on first open of existing databases
- No data loss; existing milestone/slice/task rows preserved
- Creates spec and evidence tables from existing columns (future work)
This is Phase 1 of Tier 1.3 implementation (schema definition + basic setup).
Phases 2-5 (migration, data layer updates, tool updates, tests) follow in next PRs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Document the three-phase integration of SF memory system with UOK:
Phase 1: Unit outcome recording (recordUnitOutcomeInMemory)
- Records success/failure patterns with 0.9/0.5 confidence
- Fire-and-forget async, never blocks execution
Phase 2: Dispatch ranking enhancement (enhanceUnitRankingWithMemory)
- Queries memory for similar patterns
- Boosts matching candidates by up to 15% (conservative limit)
- Deterministic embeddings ensure reproducible ranking
Phase 3: Gate context enrichment (enrichGateResultWithMemory)
- Diagnostic only; never changes gate pass/fail logic
- Helps operators understand recurring issues
All memory operations gracefully degrade if DB unavailable.
56 test cases validate integration across all phases.
Relates to ADR-0075 (UOK gates), ADR-008 (SF tools).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Add architecture decision: Memory is not exposed as MCP server.
- SF is an MCP client only (consumes external MCP tools)
- Memory is internal SF infrastructure (uses SQLite, fire-and-forget async)
- Memory exposed as SF tools only (capture, query, graph)
- No external MCP exposure needed (memory is autonomous learning, not a service)
This keeps SF's learning system private and prevents:
- External memory pollution
- Uncontrolled confidence scoring
- Inconsistent learning patterns
- Loss of autonomy (memory decisions stay internal)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Comprehensive guide for migrating from JSON to node:sqlite when Node 24 is available:
- Schema design (model_outcomes + model_stats tables)
- Phase-by-phase refactoring approach
- Data migration from JSON with backward compatibility
- Testing strategy with new SQLite-specific tests
- Future opportunities: dashboards, trend analysis, A/B testing, federated learning
This doc serves as a roadmap for ~2 days of work when Node 24 becomes standard.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Integration of 3 quick wins into existing UOK infrastructure:
1. Model Learning (Quick Win #2) → metrics.js
- Record outcomes to model-learner for per-task-type performance tracking
- Hook: recordUnitOutcome() now calls ModelLearner.recordOutcome()
- Fire-and-forget: never blocks outcome recording on learning failure
- Enables adaptive model routing decisions in downstream gates
2. Self-Report Fixing (Quick Win #1) → triage-self-feedback.js
- Auto-fix high-confidence reports (>0.85) in applyTriageReport()
- Hook: After triage and requirement promotion, apply auto-fixes
- Fire-and-forget: never blocks report application on fix failure
- Returns reportsAutoFixed count for triage metrics
3. Knowledge Injection (Quick Win #3) → already integrated in auto-prompts.js
- Already active in execute-task prompt template
- Semantic matching with graceful degradation
All integration points:
- Fire-and-forget: learning/fixing failures never block dispatch
- UOK-native: use existing outcome recording, db, gates
- Backward compatible: applyTriageReport now async, but callers handle it
- No new dependencies: all modules already in codebase
Testing: 2934 tests pass (no regressions from integration)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
