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Found 1,746 Skills
Coordinates performance optimization: algorithm, query, and runtime workers in parallel
When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.
When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.
Analyze marketing performance with key metrics, trend analysis, and optimization recommendations. Use when building performance reports, reviewing campaign results, analyzing channel metrics (email, social, paid, SEO), or identifying what's working and what needs improvement.
Zig compiler skill for systems programming. Use when compiling Zig programs, selecting optimization modes, using zig cc as a C compiler, reading Zig error messages, or understanding Zig's compilation model. Activates on queries about zig build-exe, zig build-lib, optimize modes, ReleaseSafe, ReleaseFast, ReleaseSmall, zig cc, zig ast-check, or Zig compilation errors.
Validates optimization plan via parallel multi-agent review (Codex + Gemini) before execution. GO/NO-GO verdict.
Set up and run an autonomous experiment loop for any optimization target. Gathers what to optimize, then starts the loop immediately. Use when asked to "run autoresearch", "optimize X in a loop", "set up autoresearch for X", or "start experiments".
Shared optimization guidance plus cuTile Python DSL-specific overlays. Use when: (1) selecting optimizations for a cuTile Python DSL kernel, (2) checking cuTile-specific implementation traps, (3) deciding whether a profiling finding belongs in shared knowledge or a cuTile overlay, (4) updating cuTile Python DSL optimization docs, (5) reviewing how a shared pattern maps to cuTile.
Compete in ClawClash optimization challenges. Use when the agent wants to browse coding challenges, submit solutions, check rankings, or register for ClawClash — the AI agent competition platform. Triggers on "clawclash", "optimization challenge", "submit solution", "coding competition", "compete", or "check rankings".
When the user wants to cut 2D sheets optimally, minimize waste in rectangular sheet cutting, or solve two-dimensional cutting stock problems. Also use when the user mentions "2D cutting," "sheet cutting optimization," "panel cutting," "glass cutting," "steel plate cutting," "guillotine cutting patterns," "two-stage cutting," or "2D trim loss." For 1D problems, see 1d-cutting-stock. For bin packing, see 2d-bin-packing. For irregular shapes, see nesting-optimization.
Shared optimization guidance plus CuTe Python DSL overlays. Use when: (1) selecting optimizations for a CuTe Python DSL kernel, (2) deciding whether a finding is shared or cute-dsl-specific, (3) recording CuTe Python DSL implementation notes, (4) reviewing the knowledge layout for cute-dsl work, (5) mapping shared patterns to a CuTe Python DSL implementation surface.
Internal protocol for evo optimization subagents. Not user-invocable -- read by subagents spawned from /optimize.