# Team Performance Optimization -- CSV Schema ## Master CSV: tasks.csv ### Column Definitions #### Input Columns (Set by Decomposer) | Column | Type | Required | Description | Example | |--------|------|----------|-------------|---------| | `id` | string | Yes | Unique task identifier (PREFIX-NNN) | `"PROFILE-001"` | | `title` | string | Yes | Short task title | `"Profile performance"` | | `description` | string | Yes | Detailed task description (self-contained) with goal, inputs, outputs, success criteria | `"Profile application performance..."` | | `role` | enum | Yes | Worker role: `profiler`, `strategist`, `optimizer`, `benchmarker`, `reviewer` | `"profiler"` | | `bottleneck_type` | string | No | Performance bottleneck category: CPU, MEMORY, IO, NETWORK, RENDERING, DATABASE | `"CPU"` | | `priority` | enum | No | P0 (Critical), P1 (High), P2 (Medium), P3 (Low) | `"P0"` | | `target_files` | string | No | Semicolon-separated file paths to focus on | `"src/services/DataProcessor.ts"` | | `deps` | string | No | Semicolon-separated dependency task IDs | `"PROFILE-001"` | | `context_from` | string | No | Semicolon-separated task IDs for context | `"PROFILE-001"` | | `exec_mode` | enum | Yes | Execution mechanism: `csv-wave` or `interactive` | `"csv-wave"` | #### Computed Columns (Set by Wave Engine) | Column | Type | Description | Example | |--------|------|-------------|---------| | `wave` | integer | Wave number (1-based, from topological sort) | `2` | | `prev_context` | string | Aggregated findings from context_from tasks (per-wave CSV only) | `"[PROFILE-001] Found 3 CPU hotspots..."` | #### Output Columns (Set by Agent) | Column | Type | Description | Example | |--------|------|-------------|---------| | `status` | enum | `pending` -> `completed` / `failed` / `skipped` | `"completed"` | | `findings` | string | Key discoveries (max 500 chars) | `"Found 3 CPU hotspots, 1 memory leak..."` | | `verdict` | string | Benchmark/review verdict: PASS, WARN, FAIL, APPROVE, REVISE, REJECT | `"PASS"` | | `artifacts_produced` | string | Semicolon-separated paths of produced artifacts | `"artifacts/bottleneck-report.md"` | | `error` | string | Error message if failed | `""` | --- ### exec_mode Values | Value | Mechanism | Description | |-------|-----------|-------------| | `csv-wave` | `spawn_agents_on_csv` | One-shot batch execution within wave | | `interactive` | `spawn_agent`/`wait`/`send_input`/`close_agent` | Multi-round individual execution | Interactive tasks appear in master CSV for dependency tracking but are NOT included in wave-{N}.csv files. --- ### Role Prefix Mapping | Role | Prefix | Stage | Responsibility | |------|--------|-------|----------------| | profiler | PROFILE | 1 | Performance profiling, baseline metrics, bottleneck identification | | strategist | STRATEGY | 2 | Optimization plan design, strategy selection, prioritization | | optimizer | IMPL / FIX | 3 | Code implementation, optimization application, targeted fixes | | benchmarker | BENCH | 4 | Benchmark execution, before/after comparison, regression detection | | reviewer | REVIEW | 4 | Code review for correctness, side effects, regression risks | --- ### Example Data ```csv id,title,description,role,bottleneck_type,priority,target_files,deps,context_from,exec_mode,wave,status,findings,verdict,artifacts_produced,error "PROFILE-001","Profile performance","PURPOSE: Profile application performance to identify bottlenecks\nTASK:\n- Detect project type (frontend/backend/CLI)\n- Trace hot code paths and CPU hotspots\n- Identify memory allocation patterns and leaks\n- Measure I/O and network latency\n- Collect quantified baseline metrics\nINPUT: Codebase under target scope\nOUTPUT: artifacts/baseline-metrics.json + artifacts/bottleneck-report.md\nSUCCESS: Ranked bottleneck list with severity, baseline metrics collected\nSESSION: .workflow/.csv-wave/perf-example-20260308","profiler","","","","","","csv-wave","1","pending","","","","" "STRATEGY-001","Design optimization plan","PURPOSE: Design prioritized optimization plan from bottleneck report\nTASK:\n- For each bottleneck, select optimization strategy\n- Prioritize by impact/effort ratio (P0-P3)\n- Define measurable success criteria per optimization\n- Assign unique OPT-IDs with non-overlapping file targets\nINPUT: artifacts/bottleneck-report.md + artifacts/baseline-metrics.json\nOUTPUT: artifacts/optimization-plan.md\nSUCCESS: Prioritized plan with self-contained OPT blocks\nSESSION: .workflow/.csv-wave/perf-example-20260308","strategist","","","","PROFILE-001","PROFILE-001","csv-wave","2","pending","","","","" "IMPL-001","Implement optimizations","PURPOSE: Implement performance optimizations per plan\nTASK:\n- Apply optimizations in priority order (P0 first)\n- Preserve existing behavior\n- Make minimal, focused changes\nINPUT: artifacts/optimization-plan.md\nOUTPUT: Modified source files\nSUCCESS: All planned optimizations applied, no functionality regressions\nSESSION: .workflow/.csv-wave/perf-example-20260308","optimizer","","","","STRATEGY-001","STRATEGY-001","csv-wave","3","pending","","","","" "BENCH-001","Benchmark improvements","PURPOSE: Benchmark before/after optimization metrics\nTASK:\n- Run benchmarks matching detected project type\n- Compare post-optimization metrics vs baseline\n- Calculate improvement percentages\n- Detect any regressions\nINPUT: artifacts/baseline-metrics.json + artifacts/optimization-plan.md\nOUTPUT: artifacts/benchmark-results.json\nSUCCESS: All target improvements met, no regressions\nSESSION: .workflow/.csv-wave/perf-example-20260308","benchmarker","","","","IMPL-001","IMPL-001","csv-wave","4","pending","","","","" "REVIEW-001","Review optimization code","PURPOSE: Review optimization changes for correctness and quality\nTASK:\n- Correctness: logic errors, race conditions, null safety\n- Side effects: unintended behavior changes, API breaks\n- Maintainability: code clarity, complexity, naming\n- Regression risk: impact on unrelated code paths\n- Best practices: idiomatic patterns, no anti-patterns\nINPUT: artifacts/optimization-plan.md + changed files\nOUTPUT: artifacts/review-report.md\nSUCCESS: APPROVE verdict (no Critical/High findings)\nSESSION: .workflow/.csv-wave/perf-example-20260308","reviewer","","","","IMPL-001","IMPL-001","csv-wave","4","pending","","","","" ``` --- ### Column Lifecycle ``` Decomposer (Phase 1) Wave Engine (Phase 2) Agent (Execution) --------------------- -------------------- ----------------- id ----------> id ----------> id title ----------> title ----------> (reads) description ----------> description ----------> (reads) role ----------> role ----------> (reads) bottleneck_type--------> bottleneck_type--------> (reads) priority ----------> priority ----------> (reads) target_files----------> target_files----------> (reads) deps ----------> deps ----------> (reads) context_from----------> context_from----------> (reads) exec_mode ----------> exec_mode ----------> (reads) wave ----------> (reads) prev_context ----------> (reads) status findings verdict artifacts_produced error ``` --- ## Output Schema (JSON) Agent output via `report_agent_job_result` (csv-wave tasks): ```json { "id": "PROFILE-001", "status": "completed", "findings": "Found 3 CPU hotspots: O(n^2) in DataProcessor.processRecords (Critical), unoptimized regex in Validator.check (High), synchronous file reads in ConfigLoader (Medium). Memory baseline: 145MB peak, 2 potential leak sites.", "verdict": "", "artifacts_produced": "artifacts/baseline-metrics.json;artifacts/bottleneck-report.md", "error": "" } ``` Interactive tasks output via structured text or JSON written to `interactive/{id}-result.json`. --- ## Discovery Types | Type | Dedup Key | Data Schema | Description | |------|-----------|-------------|-------------| | `bottleneck_found` | `data.location` | `{type, location, severity, description}` | Performance bottleneck identified | | `hotspot_found` | `data.file+data.function` | `{file, function, cpu_pct, description}` | CPU hotspot detected | | `memory_issue` | `data.file+data.type` | `{file, type, size_mb, description}` | Memory leak or bloat | | `io_issue` | `data.operation` | `{operation, latency_ms, description}` | I/O performance issue | | `db_issue` | `data.query` | `{query, latency_ms, description}` | Database performance issue | | `file_modified` | `data.file` | `{file, change, lines_added}` | File change recorded | | `metric_measured` | `data.metric+data.context` | `{metric, value, unit, context}` | Performance metric measured | | `pattern_found` | `data.pattern_name+data.location` | `{pattern_name, location, description}` | Code pattern identified | | `artifact_produced` | `data.path` | `{name, path, producer, type}` | Deliverable created | ### Discovery NDJSON Format ```jsonl {"ts":"2026-03-08T10:00:00Z","worker":"PROFILE-001","type":"bottleneck_found","data":{"type":"CPU","location":"src/services/DataProcessor.ts:145","severity":"Critical","description":"O(n^2) nested loop in processRecords, 850ms for 10k records"}} {"ts":"2026-03-08T10:01:00Z","worker":"PROFILE-001","type":"hotspot_found","data":{"file":"src/services/DataProcessor.ts","function":"processRecords","cpu_pct":42,"description":"Accounts for 42% of CPU time in profiling run"}} {"ts":"2026-03-08T10:02:00Z","worker":"PROFILE-001","type":"metric_measured","data":{"metric":"response_time_p95","value":1250,"unit":"ms","context":"GET /api/dashboard"}} {"ts":"2026-03-08T10:15:00Z","worker":"IMPL-001","type":"file_modified","data":{"file":"src/services/DataProcessor.ts","change":"Replaced O(n^2) with Map lookup O(n)","lines_added":12}} {"ts":"2026-03-08T10:25:00Z","worker":"BENCH-001","type":"metric_measured","data":{"metric":"response_time_p95","value":380,"unit":"ms","context":"GET /api/dashboard (after optimization)"}} ``` > Both csv-wave and interactive agents read/write the same discoveries.ndjson file. --- ## Cross-Mechanism Context Flow | Source | Target | Mechanism | |--------|--------|-----------| | CSV task findings | Interactive task | Injected via spawn message or send_input | | Interactive task result | CSV task prev_context | Read from interactive/{id}-result.json | | Any agent discovery | Any agent | Shared via discoveries.ndjson | --- ## Validation Rules | Rule | Check | Error | |------|-------|-------| | Unique IDs | No duplicate `id` values | "Duplicate task ID: {id}" | | Valid deps | All dep IDs exist in tasks | "Unknown dependency: {dep_id}" | | No self-deps | Task cannot depend on itself | "Self-dependency: {id}" | | No circular deps | Topological sort completes | "Circular dependency detected involving: {ids}" | | context_from valid | All context IDs exist and in earlier waves | "Invalid context_from: {id}" | | exec_mode valid | Value is `csv-wave` or `interactive` | "Invalid exec_mode: {value}" | | Description non-empty | Every task has description | "Empty description for task: {id}" | | Status enum | status in {pending, completed, failed, skipped} | "Invalid status: {status}" | | Role valid | role in {profiler, strategist, optimizer, benchmarker, reviewer} | "Invalid role: {role}" | | Verdict enum | verdict in {PASS, WARN, FAIL, APPROVE, REVISE, REJECT, ""} | "Invalid verdict: {verdict}" | | Cross-mechanism deps | Interactive to CSV deps resolve correctly | "Cross-mechanism dependency unresolvable: {id}" |