
Use when reviewing Python code for performance issues: identifying caching opportunities in pure functions, finding uncompiled regex patterns, profiling hot spots with real test suites, or validating optimization claims. Runs standalone or as sub-agent of bx_review_anal orchestrator.
Use when asked to rate, score, audit, or improve code quality of a project, when user wants a 0-10 quality assessment, or when asked what needs to change to reach perfect quality
Use when configuring, managing, or troubleshooting Proxmox VE - installation, host administration, clusters, VMs, containers, storage, Ceph, SDN, firewall, user management, HA, backups, notifications, and CLI tools. Covers Proxmox VE 9.1.2.
Use when building transparent remote procedure calls, distributed computing, or remote object proxying in Python with RPyC. Use when asked about rpyc.connect, rpyc.Service, netref proxies, async_(), BgServingThread, SSLAuthenticator, DeployedServer, or rpyc_classic.py.
Textual TUI framework documentation reference
Use when creating new skills, editing existing skills, structuring SKILL.md files, writing skill frontmatter, testing skills with subagents, deploying skills, or verifying skills work before deployment
Use when structuring Python 3.10+ projects with layered ports-and-adapters architecture, reviewing layer dependency violations, scaffolding domain-driven designs, deciding where code belongs across domain, application, adapter, and composition layers, or setting up ports, UoW, outbox, and idempotency patterns
Use when choosing Python libraries for a task, when writing new Python code that needs dependencies, when reviewing Python imports for non-preferred libraries, or when unsure which library to use for JSON, HTTP, logging, TOML, YAML, compression, database access, testing, or CLI tools
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide (February 2026 revision). Detects and fixes 35 patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, opinion overgeneralization, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, section summaries, placeholder text, Markdown artifacts, table overuse, subject lines, and ChatGPT-specific reference bugs.
Entfernt Anzeichen von KI-generiertem Text aus deutschsprachigen Texten. Verwende diesen Skill beim Bearbeiten oder Überprüfen von Texten, um sie natürlicher und menschlicher klingen zu lassen. Basiert auf der deutschen Wikipedia-Seite "Anzeichen für KI-generierte Inhalte" und dem englischen Pendant "Signs of AI writing". Erkennt und korrigiert 32 Muster wie: aufgeblähte Symbolik, Werbesprache, oberflächliche Partizip-Analysen, vage Autoritäten, Gedankenstrich-Übergebrauch, Trikolon, KI-typische Konjunktionen, negative Parallelismen, Fazit-Abschnitte, formelhafte Schlussfolgerungen und kollaborative Kommunikationsartefakte.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when structuring Bash 4.3+ scripts or multi-file projects with clean architecture, reviewing layer dependency violations in shell scripts, deciding where functions belong across domain, application, adapter, and composition layers, or setting up ports and dependency inversion in bash
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Use when you have a spec or requirements for a multi-step task, before touching code
Use when writing, reviewing, or debugging Bash scripts, when needing exact syntax for shell constructs, parameter expansions, redirections, builtins, test expressions, arrays, or any Bash 5.3 feature. Use when unsure about quoting rules, expansion order, conditional operators, trap behavior, shopt options, or specific builtin options and arguments.