performance

Performance Orchestrator

Static-analysis-first performance optimization workflow. Identifies bottlenecks by reading code, then uses the standard specification/planning/implementation/verification pipeline to fix them.

Initialization

BEFORE executing any phase, you MUST complete these steps:

Step 1: Load Framework Patterns

Read the framework reference file NOW using the Read tool:

1. ../orchestrator-framework/references/orchestrator-patterns.md - Delegation rules, interactive mode, state schema, initialization, context passing, issue resolution

Step 2: Initialize Workflow

1. Create Task Items: Use TaskCreate for all phases (see Phase Configuration), then set dependencies with TaskUpdate addBlockedBy
2. Create Task Directory: .maister/tasks/performance/YYYY-MM-DD-task-name/
3. Create Subdirectories: analysis/, analysis/user-profiling-data/, implementation/, verification/
4. Initialize State: Create orchestrator-state.yml with performance context

Output:

Performance Orchestrator Started

Task: [performance issue description]
Directory: [task-path]

Starting Phase 1: Codebase Analysis...

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When to Use

Use for:

• Application slow (response time issues, high latency)
• Need systematic bottleneck identification and resolution
• Want static code analysis for performance anti-patterns
• Have user-provided profiling data to act on
• Database query optimization needed
• Algorithm or I/O inefficiencies suspected

DO NOT use for: New features, bug fixes, refactoring without performance goals.

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Core Principles

1. Static Analysis First: Read code to detect patterns. Don't try to run profiling tools.
2. User Data Welcome: Incorporate user-provided profiling data when available
3. Reuse Standard Phases: Use proven specification/planning/implementation/verification pipeline
4. Conservative Estimates: Provide improvement ranges, not false precision
5. Practical Optimizations: Focus on patterns the agent CAN detect and fix

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Phase Configuration

Phase	content	activeForm	Agent/Skill
1	"Analyze codebase"	"Analyzing codebase"	codebase-analyzer
2	"Analyze performance bottlenecks"	"Analyzing performance bottlenecks"	bottleneck-analyzer
3	"Gather requirements & create specification"	"Gathering requirements & creating specification"	specification-creator
4	"Audit specification"	"Auditing specification"	spec-auditor (conditional)
5	"Plan implementation"	"Planning implementation"	implementation-planner
6	"Execute implementation"	"Executing implementation"	implementation-plan-executor
7	"Prompt verification options"	"Prompting verification options"	Direct
8	"Verify implementation & resolve issues"	"Verifying implementation"	implementation-verifier
9	"Finalize workflow"	"Finalizing workflow"	Direct

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Workflow Phases

Phase 1: Codebase Analysis & Clarifications

Purpose: Comprehensive codebase exploration for performance context, followed by scope/requirements clarification Execute:

1. Skill tool - maister-codebase-analyzer
2. Update state with analysis results
3. Direct - use ask_user for max 5 critical clarifying questions about performance concerns, hotspots, and optimization goals
4. Save clarifications to analysis/clarifications.md Output: analysis/codebase-analysis.md, analysis/clarifications.md State: Update performance_context.phase_summaries.codebase_analysis, task_context.clarifications_resolved

Pass task_type="enhancement" and the performance-focused description. The codebase-analyzer adaptively selects parallel Explore agents based on task complexity. For performance tasks, the description should guide agents toward: database query patterns, hot code paths, I/O operations, caching layers, connection management, schema/migration files.

→ AUTO-CONTINUE — Do NOT end turn, do NOT prompt user. Proceed immediately to Phase 2.

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Phase 2: Static Performance Analysis

Purpose: Identify bottlenecks through static code analysis + optional user profiling data Execute: Task tool - maister-bottleneck-analyzer subagent Output: analysis/performance-analysis.md State: Update performance_context.bottlenecks_identified, performance_context.user_data_available, performance_context.bottleneck_priorities

Process:

1. Check if analysis/user-profiling-data/ contains any files
2. If empty, use ask_user:
   • Question: "Do you have profiling data to provide (flame graphs, APM screenshots, slow query logs)?"
   • Options: "Yes, let me add files to analysis/user-profiling-data/" | "No, proceed with static analysis only"
3. If user chooses to add files, wait for them, then proceed

ANTI-PATTERN — DO NOT DO THIS:

• ❌ "Let me analyze the bottlenecks myself..." — STOP. Delegate to bottleneck-analyzer.
• ❌ "I'll grep for N+1 patterns..." — STOP. Delegate to bottleneck-analyzer.

INVOKE NOW — Task tool call:

4. Task tool - maister-bottleneck-analyzer subagent

Context to pass: task_path, description, codebase analysis summary from Phase 1, user data paths (if any)

SELF-CHECK: Did you just invoke the Task tool with maister-bottleneck-analyzer? Or did you start analyzing code yourself? If the latter, STOP and invoke the Task tool.

→ Pause

ask_user - "Performance analysis complete. [N] bottlenecks identified ([P0 count] P0, [P1 count] P1). Continue to specification?"

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Phase 3: Requirements & Specification

Phase gate: Requires ask_user confirmation from Phase 2 before executing.

Purpose: Gather optimization requirements and create specification Output: analysis/requirements.md, implementation/spec.md State: Update performance_context.phase_summaries.specification

Part A — Requirements Gathering (inline):

1. Present bottleneck summary from Phase 2 to user
2. Use ask_user for optimization priorities:
   • Which bottleneck priorities to address? (All P0+P1, P0 only, specific ones)
   • Any constraints? (backward compatibility, memory limits, no new dependencies)
   • Performance targets? (specific response time goals, if known)
3. Save gathered requirements to analysis/requirements.md with: performance issue description, bottleneck analysis summary, optimization priorities, constraints, targets

Part B — Specification Creation (subagent):

📋 Standards Discovery: Read .maister/docs/INDEX.md before creating spec.

ANTI-PATTERN — DO NOT DO THIS:

• ❌ "Let me create the specification..." — STOP. Delegate to specification-creator.
• ❌ "I'll write the spec based on the analysis..." — STOP. Delegate to specification-creator.

INVOKE NOW — Task tool call:

4. Task tool - maister-specification-creator subagent

Context to pass: task_path, task_type="performance", task_description, requirements_path (analysis/requirements.md), project_context_paths (INDEX.md, vision.md, roadmap.md, tech-stack.md), phase_summaries (codebase_analysis, bottleneck_analysis)

SELF-CHECK: Did you just invoke the Task tool with maister-specification-creator? Or did you start writing spec.md yourself? If the latter, STOP and invoke the Task tool.

→ Pause

ask_user - Display executive summary before asking. Read implementation/spec.md and extract: optimization targets, approach chosen, number of changes planned, expected impact. Format as brief overview then "Continue to specification audit?"

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Phase 4: Specification Audit (Conditional)

Phase gate: Requires ask_user confirmation from Phase 3 before executing.

Purpose: Independent review of optimization specification Execute: Task tool - maister-spec-auditor subagent Output: verification/spec-audit.md State: Update options.spec_audit_enabled

Run if: >5 optimizations planned, spec >50 lines, or user requests Skip if: Simple optimization (1-3 changes)

ask_user to decide - "Run specification audit?"

→ Pause

ask_user - Display executive summary before asking. Read verification/spec-audit.md and extract: overall verdict, issue counts by severity, top findings. Format as brief overview then "Continue to implementation planning?"

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Phase 5: Implementation Planning

Phase gate: Requires ask_user confirmation from Phase 4 before executing.

Purpose: Break optimization specification into implementation steps

📋 Standards Discovery: Read .maister/docs/INDEX.md before planning.

ANTI-PATTERN — DO NOT DO THIS:

• ❌ "Let me create the implementation plan..." — STOP. Delegate to implementation-planner.
• ❌ "I'll break this into optimization steps..." — STOP. Delegate to implementation-planner.

INVOKE NOW — Task tool call:

Execute: Task tool - maister-implementation-planner subagent Output: implementation/implementation-plan.md State: Update task groups and dependencies

Context to pass: task_path, task_type="performance", task_description, phase_summaries (specification, bottleneck_analysis, codebase_analysis)

SELF-CHECK: Did you just invoke the Task tool with maister-implementation-planner? Or did you start writing the plan yourself? If the latter, STOP and invoke the Task tool.

→ Pause

ask_user - Display executive summary before asking. Read implementation/implementation-plan.md and extract: number of task groups, total steps, key dependencies, optimization sequence. Format as brief overview then "Continue to implementation?"

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Phase 6: Implementation

Phase gate: Requires ask_user confirmation from Phase 5 before executing.

Purpose: Execute the optimization plan

📋 Standards Discovery: Implementation reads .maister/docs/INDEX.md continuously.

ANTI-PATTERN — DO NOT DO THIS:

• ❌ "Let me implement this directly..." — STOP. Delegate to implementation-plan-executor.
• ❌ "This is simple enough to code inline..." — STOP. Simplicity is NOT a reason to skip delegation.

INVOKE NOW — Skill tool call:

Execute: Skill tool - maister-implementation-plan-executor Output: Implemented optimizations, implementation/work-log.md State: Update implementation progress, extract phase_summaries.implementation

SELF-CHECK: Did you just invoke the Skill tool with maister-implementation-plan-executor? Or did you start writing code yourself? If the latter, STOP immediately and invoke the Skill tool instead.

⚠️ POST-IMPLEMENTATION CONTINUATION — After the skill completes and returns control:

1. Read orchestrator-state.yml to confirm you are the orchestrator
2. Update state: add Phase 6 to completed_phases
3. Proceed to Phase 7

→ Pause

ask_user - Display executive summary before asking. Extract from phase_summaries.implementation and implementation/work-log.md: optimizations applied, files changed, test results, any known issues. Format as brief overview then "Continue to verification?"

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Phase 7: Verification Options

Phase gate: Requires ask_user confirmation from Phase 6 before executing.

Purpose: Determine which verification checks to run Execute: Direct - use ask_user for options Output: Updated state with verification options State: Set options.code_review_enabled, options.pragmatic_review_enabled, options.production_check_enabled, options.reality_check_enabled

Always enabled: Reality check, pragmatic review Auto-set: skip_test_suite: true (full test suite already passed during implementation phase; cleared before re-verification if fixes are applied)

ask_user with sequential single-select - "Which additional verification checks?"

• "Code review" (recommended)
• "Production readiness check"

→ Pause

ask_user - "Options selected. Continue to Phase 8?"

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Phase 8: Verification & Issue Resolution

Phase gate: Requires ask_user confirmation from Phase 7 before executing.

Purpose: Comprehensive implementation verification with user-driven fix cycles Output: verification/implementation-verification.md, optional review reports State: Update verification_context

Execute:

Step 1: Invoke Skill tool - maister-implementation-verifier

Step 2: Display detailed issue breakdown grouped by category and severity (critical/warning/info), listing location, description, and fixability for each.

Step 3: Gate on verification status:

• status: passed → skip to Pause
• status: passed_with_issues or failed → enter user-driven fix loop (Step 4)

Step 4: User-driven fix loop (max 3 iterations):

1. Present all critical + warning issues as a numbered list
2. ask_user — "Which issues should I fix?" with options: "Fix all fixable issues" / "Let me choose specific issues" / "Skip fixes, proceed as-is"
3. Fix selected issues
4. After fixes: set skip_test_suite: false (code changed, tests must re-run)
5. ask_user — "Re-run verification to check fixes?" with options: "Yes, re-run verification" / "No, proceed to next phase"
6. If re-run → re-invoke maister-implementation-verifier → return to Step 2

→ Pause

ask_user - Display executive summary: total issues found, issues fixed, issues remaining by severity. Then "Continue to finalization?"

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Phase 9: Finalization

Phase gate: Requires ask_user confirmation from Phase 8 before executing.

Purpose: Complete workflow and provide next steps Execute: Direct - create summary, update state, guide commit Output: Workflow summary State: Set task.status: completed

Process:

1. Create workflow summary (bottlenecks found, optimizations implemented, verification result)
2. Update task status to "completed"
3. Provide commit message template
4. Guide performance-specific next steps:
   • Run the application and verify improvements manually
   • Consider profiling with runtime tools to measure actual impact
   • Monitor production metrics after deployment
   • Address remaining P2/P3 bottlenecks if needed

→ End of workflow

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Domain Context (State Extensions)

Performance-specific fields in orchestrator-state.yml:

performance_context:
  bottlenecks_identified: null    # count from bottleneck-analyzer
  user_data_available: false      # whether user provided profiling data
  bottleneck_priorities:
    p0: 0
    p1: 0
    p2: 0
    p3: 0
  phase_summaries:
    codebase_analysis: {key_files: [], summary: null}
    bottleneck_analysis: {bottlenecks: [], summary: null, user_data_incorporated: false}
    specification: {summary: null}

verification_context:
  last_status: null
  issues_found: null
  fixes_applied: []
  decisions_made: []
  reverify_count: 0

options:
  spec_audit_enabled: null
  skip_test_suite: true
  code_review_enabled: true
  pragmatic_review_enabled: true
  reality_check_enabled: true
  production_check_enabled: null

---

Task Structure

.maister/tasks/performance/YYYY-MM-DD-task-name/
├── orchestrator-state.yml
├── analysis/
│   ├── codebase-analysis.md           # Phase 1
│   ├── performance-analysis.md        # Phase 2
│   ├── user-profiling-data/           # Optional user-provided data
│   └── requirements.md                # Phase 3
├── implementation/
│   ├── spec.md                        # Phase 3
│   ├── implementation-plan.md         # Phase 5
│   └── work-log.md                    # Phase 6
└── verification/
    ├── spec-audit.md                  # Phase 4 (conditional)
    └── implementation-verification.md # Phase 8

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Auto-Recovery

Phase	Max Attempts	Strategy
1	2	Expand search scope, prompt user for hints
2	2	Re-analyze with broader patterns, ask user
3	2	Regenerate spec with adjusted requirements
5	2	Regenerate plan
6	5	Fix syntax, imports, tests
8	3	Fix-then-reverify cycles

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Command Integration

Invoked via:

• /maister-performance [description] (new)
• /maister-performance [task-path] [--from=PHASE] (resume)

Task directory: .maister/tasks/performance/YYYY-MM-DD-task-name/