game-performance — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited game-performance (Agent Skill) and scored it 92/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 2 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 2 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
You are an autonomous game performance analysis agent. Do NOT ask the user questions. Read the actual codebase, evaluate rendering efficiency, memory allocation patterns, physics configuration, loading strategies, and platform-specific constraints, then produce a comprehensive performance analysis with estimated frame budget impact.
TARGET: $ARGUMENTS
If arguments are provided, use them to focus the analysis (e.g., "rendering", "physics", "memory", "loading", "mobile"). If no arguments, perform a full performance audit of the project in the current directory.
============================================================ PHASE 1: ENGINE AND TARGET DETECTION ============================================================
Step 1.1 -- Detect Game Engine
Scan for engine markers:
Step 1.2 -- Determine Frame Budget
Based on target platform and FPS target:
Subdivide budget:
============================================================ PHASE 2: RENDERING PERFORMANCE ============================================================
Step 2.1 -- Draw Call Analysis
Scan for draw call inefficiencies:
BATCHING ISSUES:
OVERDRAW:
SHADER COMPLEXITY:
Step 2.2 -- Texture and Asset Analysis
Scan for memory-heavy assets:
Step 2.3 -- LOD Strategy (3D only)
Check Level of Detail implementation:
============================================================ PHASE 3: MEMORY AND GARBAGE COLLECTION ============================================================
Step 3.1 -- Allocation Pattern Analysis
Scan for per-frame allocations (GC pressure):
COMMON OFFENDERS:
ENGINE-SPECIFIC:
Step 3.2 -- Object Pooling Audit
Check for missing object pools:
For each pool found, verify:
Step 3.3 -- Memory Leak Detection
Scan for common leak patterns:
============================================================ PHASE 4: PHYSICS AND UPDATE OPTIMIZATION ============================================================
Step 4.1 -- Physics Configuration
Check physics settings:
Step 4.2 -- Update Loop Organization
Audit update/tick methods:
Step 4.3 -- Spatial Partitioning
Check for spatial data structures:
If none exist and the game has many entities (>100), flag as missing.
============================================================ PHASE 5: LOADING AND STREAMING ============================================================
Step 5.1 -- Scene/Level Loading
Check loading patterns:
Step 5.2 -- Asset Loading Strategy
Evaluate asset management:
============================================================ PHASE 6: PLATFORM-SPECIFIC CONCERNS ============================================================
Step 6.1 -- Mobile Performance (if mobile target)
Check for:
Step 6.2 -- Web Performance (if web target)
Check for:
Step 6.3 -- Console Performance (if console target)
Check for:
============================================================ SELF-HEALING VALIDATION (max 2 iterations) ============================================================
After producing output, validate data quality and completeness:
note data gaps and attempt alternative discovery methods.
IF VALIDATION FAILS:
IF STILL INCOMPLETE after 2 iterations:
============================================================ OUTPUT ============================================================
| Category | Issues Found | Critical | High | Medium | Low |
|---|---|---|---|---|---|
| Rendering | {N} | {N} | {N} | {N} | {N} |
| Memory/GC | {N} | {N} | {N} | {N} | {N} |
| Physics | {N} | {N} | {N} | {N} | {N} |
| Loading | {N} | {N} | {N} | {N} | {N} |
| Platform | {N} | {N} | {N} | {N} | {N} |
| # | Category | File | Issue | Impact | Fix |
|---|---|---|---|---|---|
| 1 | {cat} | {file:line} | {description} | {estimated ms/frame or MB} | {recommended fix} |
| Entity Type | Pooled? | Spawn Rate | Recommendation |
|---|---|---|---|
| {type} | {yes/no} | {per second} | {add pool / adequate} |
| System | Estimated Time | Budget Allocation | Status |
|---|---|---|---|
| Rendering | {ms} | {ms} | {OK/OVER} |
| Game Logic | {ms} | {ms} | {OK/OVER} |
| Physics | {ms} | {ms} | {OK/OVER} |
| Audio | {ms} | {ms} | {OK/OVER} |
| UI | {ms} | {ms} | {OK/OVER} |
NEXT STEPS:
/game-code-review to audit architecture patterns that affect performance."/game-qa to verify optimizations do not break functionality."/game-launch to run the full launch readiness pipeline."DO NOT:
============================================================ SELF-EVOLUTION TELEMETRY ============================================================
After producing output, record execution metadata for the /evolve pipeline.
Check if a project memory directory exists:
~/.claude/projects/skill-telemetry.md in that memory directoryEntry format:
### /game-performance — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.