1.8K skills · sorted by relevance
Generate a customizable AI prompt for finding representative examples in an existing codebase. Configure analysis depth, categories, and snippets so GitHub Copilot can produce exemplars.md with real file references and explanations of coding conventions.
Explore training workflows that reduce harmful model responses using a written set of principles. The skill covers self-critique, revised training examples, and RLAIF, reinforcement learning from AI feedback, with implementation examples and hardware guidance.
Provides prompt templates for coding, writing, analysis, and creative work. Helps define the AI's role, specify the desired output, add examples and constraints, and refine requests using a practical checklist.
Set up cognee and run a first Python example that stores information and retrieves it with a question. Covers virtual environments, API key configuration, optional packages, and basic troubleshooting.
Draft or revise technical documentation in a direct, friendly style based on Modal's documentation. Lead with the concept or benefit, place a runnable example near the top, and reduce jargon and vague promotional wording.
Audits Mastra documentation against repository source and canonical writing guidance. Checks examples in context, API reference coverage, and targeted automated results, then produces an evidence-based report with findings and limitations without editing files.
Audit environment files and repository contents for possible credential leaks, then prioritize findings by severity. Plan credential replacement, improve configuration examples, and establish checks in development and delivery pipelines to reduce accidental exposure.
Build Handsontable demo pages for visual regression tests, which compare screenshots for appearance changes. It guides feature routes, URL-driven display states, sample data, and decisions about testing the same feature across framework wrappers.
Find repeated tasks in recorded activity or starred examples, then describe their steps, exceptions, and human decisions. Assess a small automation candidate using captured evidence, available tools, permissions, and clear completion criteria.
Find facts, relevant examples, and prior wording in work history to support a writing draft. Use source evidence to separate completed work from plans and opinions, verify quotations, and remove sensitive details from public drafts unless disclosure is authorized.
Develop varied ideas for names, writing angles, and problem solving by exploring five candidates internally and presenting the strongest. It also expands small example collections into diverse datasets for evaluation, training, or testing.
Assess Web3 vulnerability findings before submission by checking scope, reproducibility, prerequisites, and attack costs. Organize the root cause, measurable impact, working proof of concept, and proposed fix into an Immunefi report, with examples for comparison.
Maintain a collection of architecture decision record templates, examples, translations, and tool links. It explains which files to update for each contribution and how to review pull requests for completeness, consistent formatting, and relevant content.
Install Scenic, a language for describing scenarios with randomized conditions, into the Python environment used by CARLA. Check command-line tools and version compatibility, optionally download example scenarios and map assets, and save the installation paths.
Explore training workflows that reduce harmful model responses using a written set of principles. The skill covers self-critique, revised training examples, and RLAIF, reinforcement learning from AI feedback, with implementation examples and hardware guidance.
Create, update, or review Bifrost feature documentation for Mintlify using MDX, a format combining Markdown and components. Research the interface and backend, validate configuration examples, and organize pages with screenshot placeholders and navigation entries.
Write, review, and edit developer documentation for SDKs, libraries, and frameworks. Organize guides, API references, and code examples around readers’ tasks, checking technical claims against source code and official documentation while following the destination site’s conventions.
Answer Python questions and write code using examples fetched from pythonsheets.com. Find patterns for syntax, asynchronous tasks, networking, databases, machine learning, and distributed computing, or use topic-based questions to prepare for Python interviews.
Turn existing source code into reusable learning materials. This skill identifies architectural patterns and implementation techniques, then organizes them into a SKILL.md with structured metadata, explanatory code templates, practical examples, and validation steps.
Convert articles, tutorials, or prompt collections into reusable agent skills, with one independent capability per skill. Package portable instructions, example prompts, working demos, preview images, and validation so the methods can transfer to other projects.
Learn programming concepts through a short definition, a minimal code example, and a practical use case. Explanations adapt to experience level, highlight common mistakes, and suggest related topics and a small practice exercise.
Use concrete JSON and Markdown examples to structure Sergo tool caches, strategy histories, improvement tasks, and reports. The templates show which fields to record and how to organize findings for review.
Find STATA code examples for empirical accounting research from published replication files. Adapt regression, matching, event study, and table export syntax to your variables, with citations to the papers behind each example.
Check registration records for several domains using public RDAP APIs, which provide domain registration data. Get distinct statuses for registered names, missing records, restrictions, and uncertain results without API keys, login, or a browser.