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Found 1,215 Skills
Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices
Best practices for SciPy scientific computing, optimization, signal processing, and statistical analysis in Python
Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Gemini CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".
Build a marketing performance report with key metrics, trend analysis, wins and misses, and prioritized optimization recommendations. Use when wrapping a campaign, when preparing weekly, monthly, or quarterly channel summaries for stakeholders, or when you need data translated into an executive summary with next-period priorities.
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.
Task Closure Specification, including log generation and optimization analysis. Applicable to the closure phase after major deliverables are completed.
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.
Coordinates performance optimization: algorithm, query, and runtime workers in parallel
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".
Validates optimization plan via parallel multi-agent review (Codex + Gemini) before execution. GO/NO-GO verdict.
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.
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".