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Found 582 Skills
Executes OpenAI Codex CLI for code analysis, refactoring, and automated editing. Activates when users mention codex commands, code review requests, or automated code transformations requiring advanced reasoning models.
This skill is to be used when users request in-depth analysis, thorough thinking, or detailed breakdown of a problem. It is triggered by expressions such as: 'Help me think deeply', 'Please analyze carefully', 'Help me break it down in detail', 'Please organize my thoughts', 'Think carefully', 'Gain in-depth understanding', 'Analyze in detail', or similar phrases indicating a need for systematic thinking. This skill adopts the ReAct-Plan framework: integrating chain-of-thought reasoning with explicit global planning, dynamic prediction, and reflection to overcome short-sighted behaviors.
AI generation provenance and audit trail tracking. Records decision factors, data lineage, reasoning chains, confidence scoring, and cost tracking for AI-generated content.
This skill should be used when the user wants to invoke Codex CLI for complex coding tasks requiring high reasoning capabilities. Trigger phrases include "use codex", "ask codex", "run codex", "call codex", "codex cli", "GPT-5 reasoning", "OpenAI reasoning", or when users request complex implementation challenges, advanced reasoning, architecture design, or high-reasoning model assistance. Automatically triggers on codex-related requests and supports session continuation for iterative development.
Perform statistical modeling and regression analysis on biomedical datasets. Supports linear regression, logistic regression (binary/ordinal/multinomial), mixed-effects models, Cox proportional hazards survival analysis, Kaplan-Meier estimation, and comprehensive model diagnostics. Extracts odds ratios, hazard ratios, confidence intervals, p-values, and effect sizes. Designed to solve BixBench statistical reasoning questions involving clinical/experimental data. Use when asked to fit regression models, compute odds ratios, perform survival analysis, run statistical tests, or interpret model coefficients from provided data.
Use this skill whenever the user asks to analyze, understand, or survey an entire project, codebase, or any collection of files. Trigger phrases include "analyze a large file", "process multiple files", "comprehend this problem", "take a look at these files", "familiarize yourself with this project", or any similar request, however phrased. Also activate when the task involves processing context that exceeds what can be reasoned about in a single pass, when encountering any input larger than ~50KB that requires detailed analysis, or when the user mentions "context comprehension" or "recursive comprehension". This skill TAKES PRIORITY over your default explore subagents for any project-wide or codebase-wide analysis task.
PGA Tour, LPGA, and DP World Tour golf data via ESPN public endpoints — tournament leaderboards, scorecards, season schedules, golfer profiles/overviews, and news. Zero config, no API keys. Use when: user asks about golf scores, tournament leaderboards, scorecards, PGA Tour schedule, golfer profiles, golfer season stats, LPGA results, or golf news. Don't use when: user asks about other sports.
Comprehensive prompt and context engineering for any AI system. Four modes: (1) Craft new prompts from scratch, (2) Analyze existing prompts with diagnostic scoring and optional improvement, (3) Convert prompts between model families (Claude/GPT/Gemini/Llama), (4) Evaluate prompts with test suites and rubrics. Adapts all recommendations to model class (instruction-following vs reasoning). Validates findings against current documentation. Use for system prompts, agent prompts, RAG pipelines, tool definitions, or any LLM context design. NOT for running prompts, generating content, or building agents.
React useEffect anti-pattern detection and correction guide. Use this skill whenever writing, reviewing, or modifying any React component that contains useEffect, or when about to add a useEffect hook. Also trigger when you see patterns like "setState inside useEffect", "effect chains", "derived state in effect", or "notify parent in effect". Covers 12 specific scenarios where Effects are unnecessary or misused, with correct alternatives. Even if the useEffect looks reasonable at first glance, consult this skill to verify it's truly needed.
Use when cognee is a Python AI memory engine that transforms documents into knowledge graphs with vector and graph storage for semantic search and reasoning. Use this skill when writing code that calls cognee's Python API (add, cognify, search, memify, config, datasets, prune, session) or integrating cognee-mcp. Covers the full public API, SearchType modes, DataPoint custom models, pipeline tasks, and configuration for LLM/embedding/vector/graph providers. Do NOT use for general knowledge graph theory or unrelated Python libraries.
LoRA, full fine-tuning, DPO preference tuning, VLM training, function-calling tuning, reasoning tuning, and BYOM uploads on Together AI. Reach for it whenever the user wants to adapt a model on custom data rather than only run inference, evaluate outputs, or host an existing model.
Business logic vulnerability playbook. Use when reasoning about workflows, race conditions, price manipulation, coupon abuse, state machines, and multi-step authorization gaps.