dspy-evaluation-suite
This skill should be used when the user asks to "evaluate a DSPy program", "test my DSPy module", "measure performance", "create evaluation metrics", "use answer_exact_match or SemanticF1", mentions "Evaluate class", "comparing programs", "establishing baselines", or needs to systematically test and measure DSPy program quality with custom or built-in metrics.
dspy-finetune-bootstrap
This skill should be used when the user asks to "fine-tune a DSPy model", "distill a program into weights", "use BootstrapFinetune", "create a student model", "reduce inference costs with fine-tuning", mentions "model distillation", "teacher-student training", or wants to deploy a DSPy program as fine-tuned weights for production efficiency.
dspy-gepa-reflective
This skill should be used when the user asks to "optimize an agent with GEPA", "use reflective optimization", "optimize ReAct agents", "provide feedback metrics", mentions "GEPA optimizer", "LLM reflection", "execution trajectories", "agentic systems optimization", or needs to optimize complex multi-step agents using textual feedback on execution traces.
dspy-haystack-integration
This skill should be used when the user asks to "integrate DSPy with Haystack", "optimize Haystack prompts using DSPy", "use DSPy to improve Haystack pipeline", mentions "Haystack pipeline optimization", "combining DSPy and Haystack", "extract DSPy prompt for Haystack", or wants to use DSPy's optimization capabilities to automatically improve prompts in existing Haystack pipelines.
dspy-miprov2-optimizer
This skill should be used when the user asks to "optimize a DSPy program", "use MIPROv2", "tune instructions and demos", "get best DSPy performance", "run Bayesian optimization", mentions "state-of-the-art DSPy optimizer", "joint instruction tuning", or needs maximum performance from a DSPy program with substantial training data (200+ examples).
dspy-optimize-anything
Universal text artifact optimizer using GEPA's optimize_anything API for code, prompts, agent architectures, configs, and more
dspy-output-refinement-constraints
This skill should be used when the user asks to "refine DSPy outputs", "enforce constraints", "use dspy.Refine", "select best output", "use dspy.BestOfN", mentions "output validation", "constraint checking", "multi-attempt generation", "reward function", or needs to improve output quality through iterative refinement or best-of-N selection with custom constraints.
dspy-rag-pipeline
This skill should be used when the user asks to "build a RAG pipeline", "create retrieval augmented generation", "use ColBERTv2 in DSPy", "set up a retriever in DSPy", mentions "RAG with DSPy", "context retrieval", "multi-hop RAG", or needs to build a DSPy system that retrieves external knowledge to answer questions with grounded, factual responses.
dspy-react-agent-builder
This skill should be used when the user asks to "create a ReAct agent", "build an agent with tools", "implement tool-calling agent", "use dspy.ReAct", mentions "agent with tools", "reasoning and acting", "multi-step agent", "agent optimization with GEPA", or needs to build production agents that use tools to solve complex tasks.
dspy-signature-designer
This skill should be used when the user asks to "create a DSPy signature", "define inputs and outputs", "design a signature", "use InputField or OutputField", "add type hints to DSPy", mentions "signature class", "type-safe DSPy", "Pydantic models in DSPy", or needs to define what a DSPy module should do with structured inputs and outputs.
dspy-simba-optimizer
This skill should be used when the user asks to "optimize with SIMBA", "use Bayesian optimization", "optimize agents with custom feedback", mentions "SIMBA optimizer", "mini-batch optimization", "statistical optimization", "lightweight optimizer", or needs an alternative to MIPROv2/GEPA for programs with rich feedback signals.
dspy-advanced-module-composition
This skill should be used when the user asks to "compose DSPy modules", "use Ensemble optimizer", "combine multiple programs", "use dspy.MultiChainComparison", mentions "ensemble voting", "module composition", "sequential pipelines", or needs to build complex multi-module DSPy programs with ensemble patterns or multi-chain comparison.
dspy-custom-module-design
This skill should be used when the user asks to "create custom DSPy module", "design a DSPy module", "extend dspy.Module", "build reusable DSPy component", mentions "custom module patterns", "module serialization", "stateful modules", "module testing", or needs to design production-quality custom DSPy modules with proper architecture, state management, and testing.
dspy-debugging-observability
This skill should be used when the user asks to "debug DSPy programs", "trace LLM calls", "monitor production DSPy", "use MLflow with DSPy", mentions "inspect_history", "custom callbacks", "observability", "production monitoring", "cost tracking", or needs to debug, trace, and monitor DSPy applications in development and production.
conventional-commits
Format git commit messages following Conventional Commits 1.0.0 specification. Use when the user asks to commit changes, create a git commit, or mentions committing code. Ensures consistent, semantic commit messages that support automated changelog generation and semantic versioning.
design-principles
Guide AI-assisted UI generation toward enterprise-grade, intentional design. Use when building user interfaces, creating dashboards, designing enterprise software or SaaS applications, generating frontend code with styling, or when the user asks for design help. Enforces principles inspired by Linear, Notion, Stripe, and Vercel.
fzf
Command-line fuzzy finder for interactive filtering of any list. Use when interactively selecting files, searching command history (CTRL-R), creating selection interfaces in scripts, building interactive menus, or integrating fuzzy search with tools like ripgrep, fd, and git. Triggers on mentions of fzf, fuzzy finder, ** completion, interactive filtering, or shell keybindings CTRL-T/CTRL-R/ALT-C.
git-absorb
Automatically fold uncommitted changes into appropriate commits on a feature branch. Use when applying review feedback, fixing bugs in feature branches, or maintaining atomic commit history without manual interactive rebasing. Particularly useful for making corrections to recent commits without creating messy "fixes" commits.
git-chain
Manage and rebase chains of dependent Git branches (stacked branches). Use when working with multiple dependent PRs, feature branches that build on each other, or maintaining clean branch hierarchies. Automates the tedious process of rebasing or merging entire branch chains.
jj
Jujutsu (jj) version control system - a Git-compatible VCS with novel features. Use when working with jj repositories, managing stacked/dependent commits, needing automatic rebasing with first-class conflict handling, using revsets to select commits, or wanting enhanced Git workflows. Triggers on mentions of 'jj', 'jujutsu', change IDs, operation log, or jj-specific commands.
mermaid-cli
Generate, validate, and fix diagrams from Mermaid markup using the mermaid-cli (mmdc) tool. Use when creating flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, Gantt charts, pie charts, mindmaps, or any Mermaid-supported diagram type. Also use when validating, verifying, or fixing Mermaid diagram syntax. Triggers on mentions of mermaid, mmdc, diagram generation, diagram validation, or converting .mmd files to images/SVG/PDF.
playwright
Browser automation with Playwright for Python. Use when testing websites, taking screenshots, filling forms, scraping web content, or automating browser interactions. Triggers on browser, web testing, screenshots, selenium, puppeteer, or playwright.
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
skill-reviewer
Review and ensure skills maintain high quality standards. Use when creating new skills, updating existing skills, or auditing skill quality. Checks for progressive disclosure, mental model shift, appropriate scope, and documentation clarity.
tmux
Remote control tmux sessions for interactive CLIs (python, gdb, git add -p, etc.) by sending keystrokes and scraping pane output. Use when debugging applications, running interactive REPLs (Python, gdb, ipdb, psql, mysql, node), automating terminal workflows, interactive git commands (git add -p, git stash -p, git rebase -i), or when user mentions tmux, debugging, or interactive shells.
ultrathink
Invoke deep sequential thinking for complex problem-solving. Use when the user says 'use ultrathink', 'ultrathink', or when tackling problems that require careful step-by-step reasoning, planning, hypothesis generation, or multi-step analysis.
zellij
Terminal workspace and multiplexer for interactive CLI sessions. Use when managing terminal sessions, running interactive REPLs, debugging applications, automating terminal workflows, or when user mentions zellij, terminal multiplexer, floating panes, or session layouts. Simpler alternative to tmux with native session management.
mind-clone
Activate a Cognitive Digital Twin. Can simulate a custom subject (via core/ directory) OR load pre-installed celebrity/expert personas (from personas/ directory).
agent-history
Search and analyze Claude Code conversation history. Use when user asks about past conversations, previous solutions, what was discussed earlier, finding something from history, or analyzing usage patterns. Triggers include "what did we discuss", "find that conversation", "search history", "past sessions", "how much time", "token usage", "which tools".
conversation-search
Find and resume Claude Code conversations by searching topics or filtering by date. Returns session IDs and project paths for easy resumption via 'claude --resume'. Use when user asks "find that conversation about X", "what did we discuss", "what did we work on yesterday", "summarize today's work", "show this week's conversations", "recent projects we accomplished", or wants to locate past work by topic, date, or time period (yesterday, today, last week, specific dates).
file-to-base64
Convert files (PDF, images) to Base64 encoding with MIME type detection for API attachments. Use when you need to prepare file attachments for the FreeAgent API or any other API that requires Base64-encoded files.
ai-news-crawler
Trigger phrase \"watching news!\"; Create a JSON file named with the current timestamp only in the current directory, crawl 10 AI-related news in descending order of time and output Chinese summaries
prp-manager
Create and execute PRPs (Product Requirements Prompts) for feature implementation using Context Engineering principles. Use when planning new features, initializing PRP setup, executing existing PRPs, or when the user mentions "PRP", "feature planning", "implementation blueprint", or "context engineering". Helps achieve one-pass implementation success.
decision-tracker
Git-powered state awareness - track file changes, session context, decisions, and work history. Query what happened in previous sessions and during current session. Auto-activates for state queries and before duplicating work.
ctx:architect
Systematic architecture analysis following Understand → Research → Specify → Decompose → Plan workflow. Use for system design, solution evaluation, build vs buy decisions, and task decomposition. Activate when users say "design", "architect", "break down", "best approach", or "should I build".
ctx:worktree
Expert-level git worktree troubleshooting, cleanup, and management. Use when users have worktree issues, conflicts, cleanup needs, or questions about git worktree commands. Activate for problems like stuck worktrees, locked files, orphaned branches, or worktree removal errors.
ctx:help
Help users discover Contextune capabilities and understand how to use natural language commands. Use when users ask about Contextune features, available commands, how to use the plugin, or what they can do. Activate for questions like "what can Contextune do?", "how do I use this?", "show me examples", "what commands are available?"
ctx:parallel-expert
Expert guidance on parallel development workflows using git worktrees and multi-agent execution. Use when users mention parallel work, concurrent development, speeding up development, working on multiple features simultaneously, or scaling team productivity. Activate for questions about task decomposition, worktree management, or parallelization strategies.
ctx:performance
Analyze and optimize parallel workflow performance. Use when users report slow parallel execution, want to improve speed, or need performance analysis. Activate for questions about bottlenecks, time savings, optimization opportunities, or benchmarking parallel workflows.
ctx:researcher
Efficiently research topics using parallel agents via Contextune's /ctx:research command. Use when users ask to research, investigate, find information about topics, compare options, or evaluate libraries/tools. Activate for questions like "research best X", "what's the best library for Y", or "investigate Z".
yatl-tasks
Track multi-session work with dependencies using yatl (Yet Another Task List). Use when work spans multiple sessions, has dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.
session-memory-bootstrap
Session start bootstrap. Use this skill at the beginning of EVERY new session, before answering anything else. Purpose: load persistent user memory from the repo-root memories.md file (create it if missing), then apply it to the rest of the session. If this is not a new session, only use this skill when memory is relevant or when the user asks to remember or forget something.
cuda
CUDA kernel development, debugging, and performance optimization for Claude Code. Use when writing, debugging, or optimizing CUDA code, GPU kernels, or parallel algorithms. Covers non-interactive profiling with nsys/ncu, debugging with cuda-gdb/compute-sanitizer, binary inspection with cuobjdump, and performance analysis workflows. Triggers on CUDA, GPU programming, kernel optimization, nsys, ncu, cuda-gdb, compute-sanitizer, PTX, GPU profiling, parallel performance.
brainstorming
Proactively use when brainstorming potential solutions to difficult problems.
implement-ticket
Proactively use this skill when implementing a Jira ticket.
jira-ticket
Proactively use this skill when you need to read, create, update, or manage Jira tickets.
jj-changelog
Proactively use to generate or update a CHANGELOG.md file from Jujutsu commit history.
jujutsu-planning
Proactively use when planning a complex multi-step implementation.
planning
Proactively use when making a plan, e.g. the user says "Let's make a plan".
report-writing
Use this still to write reports.
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