3.9K skills · sorted by relevance
Analyze Windows Amcache records to investigate applications, deleted executable traces, and drivers. Extract file details, compare SHA-1 hashes with malware databases, and combine records into a timeline to support incident investigations.
Build AWS applications with managed services that reduce server administration. Follow patterns for Lambda functions, HTTP APIs, database access, and queued background processing, with guidance on deployment and delays when functions first start.
Compare a job posting with your experience to score how well the requirements match. Identify strengths, missing qualifications, and potential concerns, then plan application priorities, resume adjustments, and points to address in a cover letter.
Prepare a professional reference list for job applications, choosing people who can discuss your work. Draft permission requests and briefing materials, organize contact details, and prepare for questions employers may ask your references.
Prepare an academic CV for faculty, postdoctoral, or research applications. Organize publications, grants, teaching, and research experience, with section order and formatting adapted to the role and academic field.
Turn a plain-language app request into a technology choice, project structure, and development plan. The skill coordinates specialist agents across interface, server, and database work, with templates for web, mobile, desktop, and other applications.
Design and refine prompts for LLM applications by organizing roles, context, instructions, constraints, and output formats. Develop representative examples, manage the information supplied to the model, and evaluate changes to improve how consistently responses match expectations.
Use Phoenix to record execution traces, detailed records of an AI application's operations, and investigate problems. Evaluate answers on datasets, compare prompts and models, and set up monitoring through a self-hosted server.
Evaluate LLM application quality using automated scores, human reviews, and another language model as a judge. Compare models or prompts, establish baseline results, and detect quality drops through repeatable tests and statistical comparisons.
Design LLM applications using patterns for answers grounded in documents, agents that use tools, and prompt testing. Implementation examples also cover monitoring response quality, latency, costs, and failures during operation.
Build LlamaIndex applications that retrieve relevant material before generating answers, a method called RAG. Connect documents, websites, and databases to support document questions, conversational search, structured summaries, and checks of answer relevance and source consistency.
Build Zoom meeting integrations in Windows C++ applications, including custom interfaces and bots that run without a visible interface. Guidance covers authentication, audio and video data access, project setup, and troubleshooting callbacks through the Windows message loop.
Turn applications into a ranked shortlist using only the job’s stated criteria, with evidence for each score. Prepare candidate replies, coordinate interview times, and create an onboarding checklist while leaving hiring decisions to the owner.
Find suitable grants and bidding opportunities, check eligibility before drafting, and prepare applications or responses to requests for proposals using past submissions and actual organizational data. It also tracks submission deadlines and reporting obligations after an award.
Build and update Mastra application interfaces using existing components from @mastra/playground-ui. Follow shared visual styles, arrange layouts with Tailwind utilities, and connect themes and stylesheets while avoiding duplicated components or unsupported appearance overrides.
Create a functional application prototype from an initial idea. The workflow covers requirements, technology choices, plan approval, project setup, implementation, visual assets where needed, build verification, and instructions for starting the result.
Guide a TanStack Table migration from v8 to v9 in Lit applications. Review table construction, rendering helpers, state updates, and shared application hooks, alongside the required migration checks for the core library.
Guides authentication and access permissions for Google Cloud users and applications. It helps choose credentials for local development, production services, or external clouds, with guidance on short-lived credentials and avoiding downloaded service account keys.
Design and implement Google Cloud serverless web apps with separate presentation, application, and data layers. Produces architecture diagrams, Terraform infrastructure code, deployment instructions, and validation scripts for private networking and controlled access between layers.
Audit and strengthen security for applications running on GKE. Configure pod traffic restrictions, sandbox isolation, namespace security standards, and Secret Manager volume mounts to protect workloads at the application and namespace level.
Adjust application capacity on GKE through manual scaling, HPA for changing the number of running pods, and VPA for adjusting CPU and memory allocations. Includes configuration templates and a workflow for reviewing resource requests against actual usage.
Configure how GKE applications receive traffic from the internet or internal networks. The skill provides configuration templates for routing, load balancing, certificates, and access protection, and guides diagnosis of failed health checks, dropped requests, and TLS connection problems.
Deploy and manage applications on Cloud Run using source code or container images. Choose services for web requests, jobs for tasks that finish, or worker pools for continuous background processing, with guidance on execution settings and deployment failures.
Add DeepEval tracing to Python AI applications so execution steps appear in Confident AI. Choose a supported integration or manual @observe instrumentation, then capture inputs, outputs, step types, tags, and metadata.