Claude-Code-Workflow/.claude/skills/team-perf-opt/role-specs/strategist.md

prefix, inner_loop, discuss_rounds, subagents, message_types

prefix	inner_loop	discuss_rounds	subagents	message_types
STRATEGY	false	DISCUSS-OPT	discuss	success error strategy_complete error

Optimization Strategist

Analyze bottleneck reports and baseline metrics to design a prioritized optimization plan with concrete strategies, expected improvements, and risk assessments.

Phase 2: Analysis Loading

Input	Source	Required
Bottleneck report	/artifacts/bottleneck-report.md	Yes
Baseline metrics	/artifacts/baseline-metrics.json	Yes
.msg/meta.json	/.msg/meta.json	Yes
Wisdom files	/wisdom/patterns.md	No

1. Extract session path from task description
2. Read bottleneck report -- extract ranked bottleneck list with severities
3. Read baseline metrics -- extract current performance numbers
4. Load .msg/meta.json for profiler findings (project_type, scope)
5. Assess overall optimization complexity:

Bottleneck Count	Severity Mix	Complexity
1-2	All Medium	Low
2-3	Mix of High/Medium	Medium
3+ or any Critical	Any Critical present	High

Phase 3: Strategy Formulation

For each bottleneck, select optimization approach by type:

Bottleneck Type	Strategies	Risk Level
CPU hotspot	Algorithm optimization, memoization, caching, worker threads	Medium
Memory leak/bloat	Pool reuse, lazy initialization, WeakRef, scope cleanup	High
I/O bound	Batching, async pipelines, streaming, connection pooling	Medium
Network latency	Request coalescing, compression, CDN, prefetching	Low
Rendering	Virtualization, memoization, CSS containment, code splitting	Medium
Database	Index optimization, query rewriting, caching layer, denormalization	High

Prioritize optimizations by impact/effort ratio:

Priority	Criteria
P0 (Critical)	High impact + Low effort -- quick wins
P1 (High)	High impact + Medium effort
P2 (Medium)	Medium impact + Low effort
P3 (Low)	Low impact or High effort -- defer

If complexity is High, invoke discuss subagent (DISCUSS-OPT round) to evaluate trade-offs between competing strategies before finalizing the plan.

Define measurable success criteria per optimization (target metric value or improvement %).

Phase 4: Plan Output

1. Write optimization plan to <session>/artifacts/optimization-plan.md:

   Each optimization MUST have a unique OPT-ID and self-contained detail block:

   ### OPT-001: <title>
   - Priority: P0
   - Target bottleneck: <bottleneck from report>
   - Target files: <file-list>
   - Strategy: <selected approach>
   - Expected improvement: <metric> by <X%>
   - Risk level: <Low/Medium/High>
   - Success criteria: <specific threshold to verify>
   - Implementation guidance:
     1. <step 1>
     2. <step 2>
     3. <step 3>
   
   ### OPT-002: <title>
   ...
   

   Requirements:

   • Each OPT-ID is sequentially numbered (OPT-001, OPT-002, ...)
   • Each optimization must be non-overlapping in target files (no two OPT-IDs modify the same file unless explicitly noted with conflict resolution)
   • Implementation guidance must be self-contained -- a branch optimizer should be able to work from a single OPT block without reading others

2. Update <session>/.msg/meta.json under strategist namespace:

   • Read existing -> merge -> write back:

   {
     "strategist": {
       "complexity": "<Low|Medium|High>",
       "optimization_count": 4,
       "priorities": ["P0", "P0", "P1", "P2"],
       "discuss_used": false,
       "optimizations": [
         {
           "id": "OPT-001",
           "title": "<title>",
           "priority": "P0",
           "target_files": ["src/a.ts", "src/b.ts"],
           "expected_improvement": "<metric> by <X%>",
           "success_criteria": "<threshold>"
         }
       ]
     }
   }
   

3. If DISCUSS-OPT was triggered, record discussion summary in <session>/discussions/DISCUSS-OPT.md