# Ln 650 Persistence Performance Auditor

> Coordinates 3 specialized audit workers (query efficiency, transaction correctness, runtime performance). Researches DB/ORM/async best practices, delegates parallel audits, aggregates results into docs/project/persistence_audit.md.

- Skill: `majiayu000/ln-650-persistence-performance-auditor-3` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/ln-650-persistence-performance-auditor-3`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/ln-650-persistence-performance-auditor-3/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/ln-650-persistence-performance-auditor-3

---


> **Paths:** File paths (`shared/`, `references/`, `../ln-*`) are relative to skills repo root. If not found at CWD, locate this SKILL.md directory and go up one level for repo root.

# Persistence & Performance Auditor (L2 Coordinator)

Coordinates 3 specialized audit workers to perform database efficiency, transaction correctness, and runtime performance analysis.

## Purpose & Scope

- **Coordinates 3 audit workers** (ln-651, ln-652, ln-653) running in parallel
- Research current best practices for detected DB, ORM, async framework via MCP tools ONCE
- Pass shared context to all workers (token-efficient)
- Aggregate worker results into single consolidated report
- Write report to `docs/project/persistence_audit.md` (file-based, no task creation)
- Manual invocation by user; not part of Story pipeline
- **Independent from ln-620** (can be run separately or after ln-620)

## Workflow

1) **Discovery:** Load tech_stack.md, package manifests, detect DB/ORM/async framework, auto-discover Team ID
2) **Research:** Query MCP tools for DB/ORM/async best practices ONCE
3) **Build Context:** Create contextStore with best practices + DB-specific metadata
4) **Prepare Output:** Create output directory
5) **Delegate:** 3 workers in PARALLEL
6) **Aggregate:** Collect worker results, calculate scores
7) **Write Report:** Save to `docs/project/persistence_audit.md`

## Phase 1: Discovery

**Load project metadata:**
- `docs/project/tech_stack.md` - detect DB, ORM, async framework
- Package manifests: `requirements.txt`, `pyproject.toml`, `package.json`, `go.mod`
- Auto-discover Team ID from `docs/tasks/kanban_board.md`

**Extract DB-specific metadata:**

| Metadata | Source | Example |
|----------|--------|---------|
| Database type | tech_stack.md, docker-compose.yml | PostgreSQL 16 |
| ORM | imports, requirements.txt | SQLAlchemy 2.0 |
| Async framework | imports, requirements.txt | asyncio, FastAPI |
| Session config | grep `create_async_engine`, `sessionmaker` | `expire_on_commit=False` |
| Triggers/NOTIFY | migration files | `pg_notify('job_events', ...)` |
| Connection pooling | engine config | `pool_size=10, max_overflow=20` |

**Scan for triggers:**
```
Grep("pg_notify|NOTIFY|CREATE TRIGGER", path="alembic/versions/")
  OR path="migrations/"
→ Store: db_config.triggers = [{table, event, function}]
```

## Phase 2: Research Best Practices (ONCE)

**For each detected technology:**

| Technology | Research Focus |
|------------|---------------|
| SQLAlchemy | Session lifecycle, expire_on_commit, bulk operations, eager/lazy loading |
| PostgreSQL | NOTIFY/LISTEN semantics, transaction isolation, batch operations |
| asyncio | to_thread, blocking detection, event loop best practices |
| FastAPI | Dependency injection scopes, background tasks, async endpoints |

**Build contextStore:**
```json
{
  "tech_stack": {"db": "postgresql", "orm": "sqlalchemy", "async": "asyncio"},
  "best_practices": {"sqlalchemy": {...}, "postgresql": {...}, "asyncio": {...}},
  "db_config": {
    "expire_on_commit": false,
    "triggers": [{"table": "jobs", "event": "UPDATE", "function": "notify_job_events"}],
    "pool_size": 10
  },
  "codebase_root": "/project",
  "output_dir": "docs/project/.audit/ln-650/{YYYY-MM-DD}"
}
```

## Phase 3: Prepare Output Directory

```bash
mkdir -p {output_dir}   # No deletion — date folders preserve history
```

## Phase 4: Delegate to Workers

> **CRITICAL:** All delegations use Task tool with `subagent_type: "general-purpose"` for context isolation.

**Prompt template:**
```
Task(description: "Audit via ln-65X",
     prompt: "Execute ln-65X-{worker}-auditor. Read skill from ln-65X-{worker}-auditor/SKILL.md. Context: {contextStore}",
     subagent_type: "general-purpose")
```

**Anti-Patterns:**
- ❌ Direct Skill tool invocation without Task wrapper
- ❌ Any execution bypassing subagent context isolation

**Workers (ALL 3 in PARALLEL):**

| # | Worker | Priority | What It Audits |
|---|--------|----------|----------------|
| 1 | ln-651-query-efficiency-auditor | HIGH | Redundant queries, N-UPDATE loops, over-fetching, caching scope |
| 2 | ln-652-transaction-correctness-auditor | HIGH | Commit patterns, trigger interaction, transaction scope, rollback |
| 3 | ln-653-runtime-performance-auditor | MEDIUM | Blocking IO in async, allocations, sync sleep, string concat |

**Invocation (3 workers in PARALLEL):**
```javascript
FOR EACH worker IN [ln-651, ln-652, ln-653]:
  Task(description: "Audit via " + worker,
       prompt: "Execute " + worker + ". Read skill. Context: " + JSON.stringify(contextStore),
       subagent_type: "general-purpose")
```

**Worker Output Contract (File-Based):**

Workers write full report to `{output_dir}/{worker_id}.md` per `shared/templates/audit_worker_report_template.md`.

Workers return **minimal summary** in-context (~50 tokens):
```
Report written: docs/project/.audit/ln-650/{YYYY-MM-DD}/651-query-efficiency.md
Score: 6.0/10 | Issues: 8 (C:0 H:3 M:4 L:1)
```

## Phase 5: Aggregate Results (File-Based)

Workers wrote reports to `{output_dir}/` and returned minimal summaries. Aggregation uses **return values for numbers** and **file reads for findings tables**.

**Aggregation steps:**
1. Parse scores/counts from worker return strings (already in context)
2. Read worker report files from `{output_dir}/` for findings tables
3. Calculate overall score: average of 3 category scores
4. Sum severity counts across all workers
5. Sort findings by severity (CRITICAL → HIGH → MEDIUM → LOW)
6. Context Validation (Post-Filter)

**Context Validation:**

**MANDATORY READ:** Load `shared/references/context_validation.md`

Apply Rules 1, 6 to merged findings:
```
FOR EACH finding WHERE severity IN (HIGH, MEDIUM):
  # Rule 1: ADR/Planned Override
  IF finding matches ADR → advisory "[Planned: ADR-XXX]"

  # Rule 6: Execution Context
  IF finding.check IN (blocking_io, redundant_fetch, transaction_wide, cpu_bound):
    context = 0
    - Function in __init__/setup/bootstrap/migrate → context += 1
    - File in tasks/jobs/cron/                      → context += 1
    - Has timeout/safeguard nearby                  → context += 1
    - Small data (<100KB file, <100 items dataset)  → context += 1
    IF context >= 3 → advisory
    IF context >= 1 → severity -= 1

Downgraded findings → "Advisory Findings" section in report.
Recalculate overall score excluding advisory findings from penalty.
```

**Exempt:** Missing rollback CRITICAL, N-UPDATE loops in hot paths.

## Output Format

```markdown
## Persistence & Performance Audit Report - [DATE]

### Executive Summary
[2-3 sentences on overall persistence/performance health]

### Compliance Score

| Category | Score | Notes |
|----------|-------|-------|
| Query Efficiency | X/10 | ... |
| Transaction Correctness | X/10 | ... |
| Runtime Performance | X/10 | ... |
| **Overall** | **X/10** | |

### Severity Summary

| Severity | Count |
|----------|-------|
| Critical | X |
| High | X |
| Medium | X |
| Low | X |

### Findings by Category

#### 1. Query Efficiency

| Severity | Location | Issue | Recommendation | Effort |
|----------|----------|-------|----------------|--------|
| HIGH | job_processor.py:434 | Redundant entity fetch | Pass object not ID | S |

#### 2. Transaction Correctness

| Severity | Location | Issue | Recommendation | Effort |
|----------|----------|-------|----------------|--------|
| CRITICAL | job_processor.py:412 | Missing intermediate commits | Add commit at milestones | S |

#### 3. Runtime Performance

| Severity | Location | Issue | Recommendation | Effort |
|----------|----------|-------|----------------|--------|
| HIGH | job_processor.py:444 | Blocking read_bytes() in async | Use aiofiles/to_thread | S |

### Recommended Actions (Priority-Sorted)

| Priority | Category | Location | Issue | Recommendation | Effort |
|----------|----------|----------|-------|----------------|--------|
| CRITICAL | Transaction | ... | Missing commits | Add strategic commits | S |
| HIGH | Query | ... | Redundant fetch | Pass object not ID | S |

### Sources Consulted
- SQLAlchemy best practices: [URL]
- PostgreSQL NOTIFY docs: [URL]
- Python asyncio-dev: [URL]
```

## Phase 6: Write Report

Write consolidated report to `docs/project/persistence_audit.md` with the Output Format above.

## Critical Rules

- **Single context gathering:** Research best practices ONCE, pass contextStore to all workers
- **Parallel execution:** All 3 workers run in PARALLEL
- **Trigger discovery:** Scan migrations for triggers/NOTIFY before delegating (pass to ln-652)
- **Metadata-only loading:** Coordinator loads metadata; workers load full file contents
- **Do not audit:** Coordinator orchestrates only; audit logic lives in workers

## Definition of Done

- Tech stack discovered (DB type, ORM, async framework)
- DB-specific metadata extracted (triggers, session config, pool settings)
- Best practices researched via MCP tools
- contextStore built with output_dir = `docs/project/.audit/ln-650/{YYYY-MM-DD}`
- Output directory created (no deletion of previous runs)
- All 3 workers invoked in PARALLEL and completed; each wrote report to `{output_dir}/`
- Results aggregated from return values (scores) + file reads (findings tables)
- Compliance score calculated per category + overall
- Executive Summary included
- Report written to `docs/project/persistence_audit.md`
- Sources consulted listed with URLs

## Workers

- [ln-651-query-efficiency-auditor](../ln-651-query-efficiency-auditor/SKILL.md)
- [ln-652-transaction-correctness-auditor](../ln-652-transaction-correctness-auditor/SKILL.md)
- [ln-653-runtime-performance-auditor](../ln-653-runtime-performance-auditor/SKILL.md)

## Reference Files

- Tech stack: `docs/project/tech_stack.md`
- Kanban board: `docs/tasks/kanban_board.md`

---
**Version:** 1.0.0
**Last Updated:** 2026-02-04