Use when managing complex form state, synchronous and asynchronous input validation, or form submission transitions in BLoC.

Build, modify, debug, migrate, review, or verify TypeScript MCP servers and MCP Apps with mcp-use. Use for tools, resources, prompts, middleware, Views, authentication, Skills over MCP, scaffolding, and advanced features.

Convert, migrate, or import AWS CloudFormation stacks or templates into Pulumi programs. Load this skill whenever a user wants to move from CloudFormation to Pulumi, convert a CFN template, import existing CloudFormation-managed resources into Pulumi, or asks about CloudFormation-to-Pulumi migration in any form. Also load when the user mentions cdk-importer in a migration context.

X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics. Covers OAuth auth patterns, rate limits, and platform-native content posting. Use when the user wants to interact with X programmatically.

Review, configure, and troubleshoot prek hooks when users need prek.toml edits, shim installs, hook validation, or pre-commit migration help.

Use when designing, reviewing, or updating Codex app automations, cron jobs, scheduled tasks, recurring runs, or heartbeat follow-ups.

Review the completed slice for correctness, risk, evidence gaps, and next-stage blockers. Use when the user asks for review, PR readiness, risk assessment, blocker identification, or post-work verification.

Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.

Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware investigation.

Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.

Implements and validates existing PRP plans and corrects reviewed or failing-CI pull requests. Always use when executing an implementation plan, implementing an issue that already has a local or published plan, correcting a PR from a PRP review report or CI failure, when another PRP workflow reaches its implementation or correction step, or when the user invokes $prp-implement.

Expert guidance on Nix, NixOS, home-manager, flakes, and Nix packaging. Use when writing or debugging Nix expressions, configuring NixOS or home-manager, authoring derivations, managing flake inputs, encrypting secrets with agenix or sops-nix, or hardening a NixOS host. Triggers on Nix, NixOS, nixpkgs, home-manager, flake.nix, nixos-rebuild, nix build, nix develop, devShell, derivation, overlay, agenix, and on Nix errors such as hash mismatches, infinite recursion, or evaluation failures. Advisory rather than generative: it explains, reviews, and debugs. If the repository provides its own skill for authoring host configurations, prefer that for writing config.

Creates a draft GitHub pull request with a plain-text conventional-commit title and a succinct description of the branch. Use when the user asks to open, raise, or create a pull request or PR.

Comet Classic 工作流（OpenSpec + Superpowers）。当用户明确调用 /comet-classic、要求启动或恢复 Comet Classic，或 resume-probe 返回可无歧义恢复的 active Classic change 时使用。

Comet preset — handle a lightweight or medium change that fits one OpenSpec change.

Comet Classic workflow (OpenSpec + Superpowers). Use when the user invokes /comet-classic, asks to start or resume it, or resume-probe returns an unambiguous active Classic change.

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

Generate or edit images using AI models (FLUX, Gemini). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that isn't a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

Open Knowledge Format (OKF) v0.2 guidance. Use when creating, reading, reviewing, or maintaining an OKF bundle; responding to OpenKnowledge `okf` plugin warnings; or choosing types, provenance, links, indexes, or logs.