Results for “ats-optimization”

Professional CV and resume builder transforming career narratives into ATS-optimized, multi-format resumes. Integrates with career-biographer for data and competitive-cartographer for positioning. Generates PDF, DOCX, LaTeX, JSON Resume, HTML, and Markdown. Activate on 'resume', 'CV', 'ATS optimization', 'job application'. NOT for cover letters, portfolio websites (use web-design-expert), LinkedIn optimization, or interview preparation.

Analyze AWS resources and IaC files to generate cost optimization recommendations, creating GitHub issues for each opportunity.

Optimizes smart contract gas consumption with storage patterns, batch operations, and assembly usage

Run autonomous optimization loops that iteratively improve artifacts against evaluators using hypothesis tree refinement, without overfitting.

Analyzes AWS billing and suggests cost optimization strategies for EC2, RDS, S3, and Lambda

Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.

Use when profiling, diagnosing, or improving Three.js or WebGL game performance without regressing gameplay—frame-time drops, CPU/GPU pressure, draw calls, texture/geometry budgets, animation loops, adaptive quality, mobile performance, and browser performance verification.

Optimize Kubernetes cluster costs by right-sizing resources, configuring autoscalers, using spot instances, and monitoring spend.

Reduces AI API costs by 30-75% by classifying task complexity, checking prompt quality, and routing tasks to the most cost-efficient model tier before execution.

Optimizes code for performance - speed, memory, bundle size

Autonomous experiment loop that optimizes any file by a measurable metric. Inspired by Karpathy's autoresearch. The agent edits a target file, runs a fixed evaluation, keeps improvements (git commit), discards failures (git reset), and loops indefinitely. Use when: user wants to optimize code speed, reduce bundle/image size, improve test pass rate, optimize prompts, improve content quality (headlines, copy, CTR), or run any measurable improvement loop. Requires: a target file, an evaluation command that outputs a metric, and a git repo.

Diagnose paid-ad campaigns and draft or apply optimizations using evidence, financial constraints, and experiments. Supports budget reallocation, bid changes, creative rotation, and CPA/ROAS improvement.

Converte diagnóstico de desempenho em plano de ação priorizado por tiers, com confiança declarada e foco em uma recomendação por vez.

Optimize cloud costs across AWS, Azure, GCP, and OCI through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.

Optimizes hot-path scalar loops in .NET 8+ with cross-platform Vector128/Vector256/Vector512 SIMD intrinsics, or replaces manual math loops with single TensorPrimitives API calls.

Improves AI skills for activation, clarity, and cross-model reliability through benchmarking, salience tuning, and regression triage.

Runs an autonomous optimization loop that iteratively improves an artifact against an objective and evaluator using Hypothesis Tree Refinement, with subagent executors in isolated git worktrees.

Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.

Designs and governs recursive self-improvement loops where an agent mines its own failures and proposes edits to its own harness, prompts, or workflow, covering acceptance gates, diversity preservation, and the optimization ladder.

Use when using AWS S3.

Improve interface performance across loading speed, rendering, animations, images, and bundle size. Makes experiences faster and smoother.

Use this skill when optimizing app store listings, researching keywords, or tracking mobile app performance on Apple App Store and Google Play Store.

Extends effective context capacity through strategic compression, masking, caching, and partitioning techniques.

Audit App Store and Google Play listings for discoverability and conversion — keywords, localized metadata, screenshots, ratings prompts — then emit a prioritized ASO plan. Use when "optimize our store listing", "improve app downloads", or "ASO". Submission mechanics → plan-mobile-readiness. Plan only.

Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.

Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights, rewriting drafts to improve engagement and visibility.

A* pathfinding skill for heuristics and optimization.

Optimizes long-running agent sessions with structured context compression, summarization, and durable handoff summaries that preserve decisions, files, risks, and next actions.

Reduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.

Optimize context usage for the session by reducing bloat, improving token efficiency, and focusing on relevant areas. Use when context is growing large, responses are slow, or switching between unrelated tasks. Covers context analysis, compacting, targeted pruning, MCP-first strategies, and focused scoping by area.

Optimize the cited draft against Semrush ContentShake AI scores. Calls .claude/skills/optimize-content/scripts/contentshake_optimize.py for SEO + Quality scoring + recommendations, then judgment-rewrites the additions in brand voice. Iterates until both scores ≥ 8 or voice drift triggers a rollback. No Chrome MCP, no TipTap injection — pure API.

Use when evaluating costs or looking for ways to reduce expenses in your domain. This skill provides a framework for identifying, analyzing, and reducing costs across all operations, infrastructure, development, and business activities.

Selects and scores marketing ideas for SaaS products using a feasibility scoring system to prioritize high-impact, low-effort opportunities.

Optimizes Pine Script for performance, user experience, and visual appeal on TradingView. Use when improving script speed, reducing load time, enhancing UI, organizing inputs, improving colors and visuals, or making scripts more user-friendly. Triggers on "optimize", "improve", "faster", "better UX", "clean up", or enhancement requests.

Model, simulate, and optimize Serializer/Deserializer (SerDes) systems — serial and parallel links — using MATLAB SerDes Toolbox. Design NRZ and PAM-N links (PAM3 through PAM16) — explore equalization architectures (FFE, CTLE, DFE), sweep or optimize parameters with genetic algorithms, and characterize channels from loss models, S-parameter files, or crosstalk scenarios. Process captured waveforms through equalization chains, build eye diagrams, and decompose jitter. Deliver IBIS-AMI models for Tx, Rx, Redriver, or Retimer by exporting to Simulink and compiling .ami/.ibs/.dll/.so files. Covers the full arc from initial design exploration and parameter optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization.