Use when the user wants to build a consistent-identity LoRA for an original character — defining the character, generating a face/body-consistent multi-angle dataset (via the gpt-image-gen skill for codex image generation), captioning it, doing base-specific homework, training on a chosen base (Pony / Z-Image / others) on a local GPU, and producing a usable LoRA. This skill ORCHESTRATES the end-to-end pipeline and gates every expensive/irreversible step; it delegates actual image generation to gpt-image-gen and never improvises training settings from memory.
Use when the user asks to generate an image via GPT/Codex (e.g. 「叫 gpt 生圖」「幫我用 gpt 生圖」「gpt 畫一個 X」). The skill drafts a Chinese + English prompt pair, iterates with the user until they explicitly approve, then dispatches Codex CLI ($imagegen skill, codex built-in image_gen) in the background, monitors progress, converts the result to a jpg in the current working directory, and writes a sidecar prompt log. Does text-to-image AND img2img — drop a reference image (on-disk file) and it runs Codex `-i` to lock a face/character across scenes.
Convert a Markdown report into a presentation-quality .pptx via interactive design decisions + hand-coded build script. Use when user says '/md2ppt', 'markdown to pptx', 'make slides from this md', '簡報', '做投影片', or similar. Optional self-check loop: if LibreOffice available, renders pptx → PNG per slide and checks for overflow / tiny font / emoji / misaligned content before user review. NOT a generic auto-converter — drives a per-slide layout dialogue then emits a reusable build script. Brand-template integration is supported as ad-hoc primitives (helpers exist) but is intentionally not a prescribed workflow — every brand template differs and is best handled by direct LLM-user dialogue.
Use when the user attended one or more sessions of a conference (with audio recordings + slide photos) and needs help building (1) faithful per-session reconstructions in markdown (slide visuals + speaker transcript with Whisper hallucination annotations), and (2) a downstream report deliverable whose scope and format are decided interactively with the user. Pipeline phase (raw → mlx_whisper Chinese SRT → per-slide multimodal reconstruction → official agenda cross-check via Playwright if available) is deterministic. Report phase is interactive — always quiz user on scope (single-session / single-day / multi-day synthesis), format (existing template / free-form fallback), recipient (formal / informal), and any business workstream mapping before drafting.
Use when the user wants to lint a repo following the Karpathy LLM Wiki pattern (raw/ + wiki/ + SCHEMA.md / index.md / log.md). The skill detects path, scans wiki pages + schema layer, reports frontmatter gaps, source traceability breaks, stale claims, orphan pages, missing topics, data gaps, cross-page contradictions, and SCHEMA-vs-reality drift. Read-only — never auto-fixes, never writes to log.md, never touches the network.
Use when the user wants to lint a Claude Code memory directory (~/.claude/memory or custom path) for index inconsistency, stale project state, duplicate / conflicting feedback rules, naming convention violations, frontmatter gaps, and oversized files. The skill detects path, scans root-level *.md, reports findings by severity. Read-only — never auto-fixes, never deletes, never merges.
Spec-driven 開發流程 — 從模糊需求到驗收結案。自動判斷專案狀態，引導 user 走完：需求釐清 → 技術審查 → 實作 → 驗收 → 結案報告。
巴逆逆（8zz）反指標追蹤器 — 抓取 Threads 貼文並進行台股反指標分析。Use when user says '/banini', '巴逆逆', '反指標', '冥燈' or similar.