添加 claude code game studios 到项目

CCGS Skill Testing Framework/agents/specialists/performance-analyst.md

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+# Agent Test Spec: performance-analyst
+
+## Agent Summary
+Domain: Profiling, bottleneck identification, performance metrics tracking, and optimization recommendations.
+Does NOT own: implementing optimizations (belongs to the appropriate programmer for that domain).
+Model tier: Sonnet (default).
+No gate IDs assigned.
+
+---
+
+## Static Assertions (Structural)
+
+- [ ] `description:` field is present and domain-specific (references profiling / bottleneck analysis / performance metrics)
+- [ ] `allowed-tools:` list includes Read, Write, Edit, Bash, Glob, Grep
+- [ ] Model tier is Sonnet (default for specialists)
+- [ ] Agent definition does not claim authority over implementing any optimization — explicitly identifies itself as analysis/recommendation only
+
+---
+
+## Test Cases
+
+### Case 1: In-domain request — appropriate output
+**Input:** "Analyze this frame time data: CPU 14ms, GPU 8ms, physics 6ms, draw calls 420, scripts 3ms."
+**Expected behavior:**
+- Identifies the primary bottleneck: CPU is over a 16.67ms (60fps) budget at 14ms total
+- Breaks down contributors: physics (6ms, 43% of CPU time) is the top culprit
+- Draw calls (420) flags as a secondary concern if the budget limit is lower (e.g., 200 draw calls per technical-preferences.md)
+- Produces a prioritized bottleneck report:
+  1. Physics — 6ms, reduce simulation frequency or switch broadphase algorithm
+  2. Draw calls — 420, implement batching or LOD
+  3. Scripts — 3ms, profile hot paths
+- Does NOT implement any of these optimizations
+
+### Case 2: Out-of-domain request — redirects correctly
+**Input:** "Implement the batching optimization to reduce draw calls from 420 to under 200."
+**Expected behavior:**
+- Does NOT produce implementation code for batching
+- Explicitly states that implementing optimizations belongs to the appropriate programmer (engine-programmer for rendering batching)
+- Redirects the implementation to `engine-programmer` with the recommendation context attached
+- May produce a requirements brief for the optimization so engine-programmer has a clear target
+
+### Case 3: Regression identification
+**Input:** "Performance dropped significantly after last week's commits. Frame time went from 10ms to 18ms."
+**Expected behavior:**
+- Proposes a bisection strategy to identify the offending commit range
+- Requests or reviews the diff of commits in the window to narrow the likely cause
+- Identifies affected systems based on what changed (e.g., if physics code was modified, points to physics as the primary suspect)
+- Produces a regression report naming the probable commit, the affected system, and the measured delta
+
+### Case 4: Recommendation vs. code quality trade-off
+**Input:** "The fastest optimization for the script bottleneck would be to inline all calls and remove abstraction layers."
+**Expected behavior:**
+- Surfaces the trade-off: inlining improves performance but reduces testability and violates the coding standard requiring unit-testable public methods
+- Does NOT recommend the optimization without noting the code quality cost
+- Escalates the trade-off to `lead-programmer` for a decision
+- May propose a middle path (e.g., profile-guided inlining of only the hottest 2–3 methods) that preserves testability
+
+### Case 5: Context pass — technical-preferences.md budget
+**Input:** Technical preferences from context: Target 60fps, frame budget 16.67ms, draw calls max 200, memory ceiling 512MB. Request: "Review the current build profile."
+**Expected behavior:**
+- References the specific values from the provided context: 16.67ms, 200 draw calls, 512MB
+- Compares current measurements against each threshold explicitly
+- Labels each metric as WITHIN BUDGET / AT RISK / OVER BUDGET based on the provided numbers
+- Does NOT use different budget numbers than those provided in the context
+
+---
+
+## Protocol Compliance
+
+- [ ] Stays within declared domain (profiling, analysis, recommendations — not implementation)
+- [ ] Redirects optimization implementation to the correct programmer domain agent
+- [ ] Returns structured findings (bottleneck report with severity, measured values, and recommended action owner)
+- [ ] Escalates code-quality trade-offs to lead-programmer rather than deciding unilaterally
+- [ ] Applies budget thresholds from provided context rather than assumed defaults
+- [ ] Labels all findings with a specific action owner (who should implement the fix)
+
+---
+
+## Coverage Notes
+- Frame time analysis (Case 1) output should be structured as a report filed in `production/qa/evidence/`
+- Regression case (Case 3) confirms the agent investigates cause, not just measures symptoms
+- Code quality trade-off (Case 4) verifies the agent does not recommend optimizations that violate coding standards without flagging the conflict