tailored-resume-generator
tailored-resume-generator
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
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prompt-engineering-patterns
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
outlines
outlines
Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library
labor-productivity-optimizer
labor-productivity-optimizer
AI-powered workforce planning and task assignment skill to maximize warehouse labor efficiency
load-optimization-calculator
load-optimization-calculator
AI-powered load building and consolidation skill to maximize trailer utilization and reduce transportation costs
predictive-maintenance-scheduler
predictive-maintenance-scheduler
Predictive maintenance scheduling skill using telematics data and historical patterns to maximize fleet uptime
route-optimization-engine
route-optimization-engine
AI-powered route planning and optimization skill using advanced algorithms (VRP, TSP) to minimize transportation costs, reduce delivery times, and maximize vehicle utilization
wave-planning-optimizer
wave-planning-optimizer
Automated wave planning and pick path optimization skill to maximize warehouse throughput and order accuracy
bio-multi-omics-mixomics-analysis
bio-multi-omics-mixomics-analysis
Builds supervised and unsupervised multivariate integration across bulk omics blocks with mixOmics - sPLS for sparse pairwise correlation, DIABLO (block.splsda) for a multi-block discriminant signature, rCCA for regularized canonical correlation, and MINT for multi-study integration. Covers why these projection methods maximize covariance or correlation and…
hyperparameter-tuning
hyperparameter-tuning
Optimize machine learning model hyperparameters using grid search, random search, Bayesian optimization, and Hyperband to maximize model performance within a compute budget. Use when the user requests hyperparameter tuning or provides relevant inputs for this workflow.
logfire-instrumentation
logfire-instrumentation
Add Pydantic Logfire observability to application code — traces, logs, metrics, and AI/agent spans. Use when the user asks to add or configure Logfire, observability, tracing, logging, or monitoring; maximize useful telemetry; or understand what an app is doing. Supports Python, JavaScript/TypeScript, Rust, and major AI agent frameworks including Pydantic A…
prompt-engineering-patterns
prompt-engineering-patterns
ALWAYS use this when the request matches Prompt Engineering Patterns: Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
sbtc-yield-maximizer
sbtc-yield-maximizer
Routes idle sBTC to the highest safe live yield path and executes either capped Zest supply or a HODLMM rebalance when the winning route is safely executable.
carto-territory-planning
carto-territory-planning
Builds territory planning workflows in CARTO combining territory balancing and location allocation. Triggers when the user mentions territory balancing, territory planning, sales territories, service zones, workload distribution, balanced territories, location allocation, facility placement, optimal locations, maximize coverage, minimize cost, minimize trav…
context-maximizer
context-maximizer
Exploit the 1M token context (Opus 4.6 / Sonnet 4.6) for full codebase awareness in SpecKit. Intelligently loads constitution, specs, skills, and codebase files while staying within token limits. Prioritizes critical files and provides context usage reports.
prompt-engineering-patterns
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
outlines
outlines
Guarantee valid JSON/XML/code structure during generation, use Pydantic models for type-safe outputs, support local models (Transformers, vLLM), and maximize inference speed with Outlines - dottxt.ai's structured generation library
5-email-webinar-sales-sequence
5-email-webinar-sales-sequence
This prompt instructs the AI to act as an experienced email marketing strategist and produce a five-part webinar promotion sequence (announcement, reminder, value tip, last call, and day-of reminder) tailored to the event timeline, delivering for each email a subject line, preview text, and a complete body designed to maximize engagement, clicks, and regist…
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