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Found 36 Skills
Canonical Zener HDL semantics, package rules, manifests, and high-value stdlib APIs. Covers `Module()`, `io()`, `config()`, imports, `pcb.toml`, `pcb.sum`, stdlib interfaces and units, and package APIs.
Canonical Zener HDL semantics, package rules, manifests, and high-value stdlib APIs. Use before non-trivial `.zen` creation, editing, refactoring, or review when the task touches `Module()`, `io()`, `config()`, imports, `pcb.toml`, `pcb.sum`, stdlib interfaces or units, or unfamiliar package APIs. Read this before editing instead of guessing.
Write, edit, refactor, or review Python in easy-cheese with concise stdlib-first code, Python 3.12, self-contained .pyz packaging, and repository test and validation conventions. Use for Python changes under src/, shared/scripts/, scripts/, .github/scripts/, or tests/, especially when the user asks for Pythonic, succinct, de-slopped, dataclass-based, CLI, validator, or bundled-helper code.
Tact language for TON blockchain smart contracts — types, contracts, messages, send/receive, stdlib, and security.
Guide for cross-compiling complex C programs (like DOOM) for embedded MIPS environments with custom VM runtimes. This skill applies when building software that targets MIPS architecture with limited stdlib support, custom syscall interfaces, or JavaScript-based VM execution environments. Use when cross-compiling games, applications, or any C code for constrained MIPS targets.
Canonical X07 language + stdlib reference (mirrors `x07 guide` output) for end-user skill packs.
Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. Use when the user says "audit this codebase", "audit for over-engineering", "what can I delete from this repo", "find bloat", "ponytail-audit", or "/ponytail-audit". One-shot report, does not apply fixes.
12 production-ready regulatory affairs and quality management skills for HealthTech/MedTech: ISO 13485 QMS, MDR 2017/745, FDA 510(k)/PMA, ISO 27001 ISMS, GDPR/DSGVO compliance, risk management (ISO 14971), CAPA, document control, and internal auditing. Python tools included (all stdlib-only). Works with Claude Code, Codex CLI, and OpenClaw.
Modern, powerful structured logging for Python using structlog. Use when adding or improving logging in Python projects, configuring structlog for dev/production, working with contextvars for request-scoped logging, integrating structlog with stdlib logging, or writing tests for logging behavior.
Idiomatic Python 3.14+ development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, uv/ruff toolchain, and minimal dependencies.
Use when running an annual SaaS audit, doing category-level spend review, or rationalizing the supplier base — when the user needs to do a spend audit, spend categorization (UNSPSC-aligned), purchasing-cycle analysis, or risk-balanced supplier consolidation. Triggers on "spend audit", "SaaS audit", "spend categorization", "supplier rationalization", "supplier consolidation", "purchasing cycle", "procurement review", "category strategy", "duplicate SaaS", "renewal cluster". Ships 3 stdlib-only Python tools (UNSPSC-aligned spend categorizer with Pareto breakdown and industry profiles, purchasing-cycle analyzer that surfaces bottleneck categories per Goldratt's Theory of Constraints, supplier-consolidation planner that refuses single-source recommendations for tier-1 categories without a documented break-glass plan), 3 reference docs each citing 7+ authoritative sources (A.T. Kearney / Hackett / Spend Matters / UNSPSC / Productiv / Vendr / Tropic / IACCM / ISM / BCG), and a 20-minute spend-intake template. Distinct from sibling vendor-management (performance scoring of vendors you keep paying), finance/financial-analysis (close + report, not category strategy), and c-level-advisor/general-counsel-advisor (contract law, not category rationalization).
Create enterprise architecture diagrams using PlantUML ArchiMate stdlib macros. Best for layered EA modeling (Business/Application/Technology), motivation analysis, migration planning, and TOGAF views. Uses `!include <archimate/Archimate>` stdlib with typed element macros and relationship macros. NOT for cloud infrastructure (use cloud skill) or network topology (use network skill).