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365-skills
365-skills contains 15 collected skills from Agents365-ai, with repository-level occupation coverage and site-owned skill detail pages.
Skills in this repository
Use when the user gives a topic and wants an automated topic-driven narrated explainer, podcast, or knowledge-summary video (Bilibili / YouTube / Xiaohongshu / Douyin / WeChat Channels), or asks to learn visual design patterns from a reference video/image. Trigger when the user mentions creating a knowledge video, narrated explainer, video podcast, or talking-head topic video from a topic — even if they don't say "video podcast" explicitly. Also trigger when the user wants to regenerate, re-render, rebuild, update, or iterate on a narrated video this skill already produced — e.g. they edited the script/prompt, changed the visuals, or swapped the background music and want the final video remade (reuse the existing videos/{name}/ directory, never start a new project). Do NOT trigger for generic video editing, trimming, format conversion, color grading, or non-narrative video tasks. Produces 4K video via research → script → TTS → Remotion → MP4 + BGM.
Multi-platform Chinese & multilingual TTS text-to-speech via Edge/Doubao/CosyVoice/Azure/Tencent/Baidu/MiniMax/Xunfei plus ElevenLabs/OpenAI/Google — 11 backends, word-level timestamps, [PAUSE:x] pause markers, pinyin pronunciation overrides
Use when looking up journal impact factors (JCR IF), checking a journal's impact factor by name, comparing IF across journals, or answering questions about "影响因子" / "impact factor" / "IF". Triggers on "impact factor", "journal IF", "影响因子", "JCR", "IF score", "journal rank", "which journal has higher IF", "what is the IF of". PROACTIVELY USE when user mentions journal prestige, publication venue quality, or manuscript submission target evaluation.
Use when looking up journal or magazine name abbreviations, converting between full names and ISO 4/MEDLINE abbreviations, processing BibTeX files for journal name standardization, or answering questions about 期刊缩写/杂志缩写. Triggers on "journal abbreviation", "abbreviate journal", "journal name", "期刊缩写", "杂志缩写", "ISO 4", "LTWA", "BibTeX journal". PROACTIVELY USE when user mentions citation formatting, reference list preparation, or manuscript submission to specific journals.
File new notes into the right folder and audit/reorganize folder structure in the user's Obsidian vault, using the `obsidian` CLI and a single source-of-truth map note (`00_Index/Folder_Map.md`) that lives inside the vault. Use this whenever a note needs to be placed, filed, sorted, or moved into the vault; whenever the user asks where a note "belongs" or "should go"; and whenever they want to clean up, reorganize, deduplicate, audit, or restructure vault folders (e.g. orphaned notes, dead-end notes, near-duplicate titles, overlapping folders). Trigger even when the user just says "add this to my vault", "put this somewhere sensible", or "tidy up the cellchat notes" without naming a folder. Requires the Obsidian desktop app to be running.
Use when designing, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.
Use when designing, reviewing, or refactoring a CLI that must serve AI agents alongside humans, or when converting an API or SDK into an agent-usable CLI interface.
Use when generating images with Alibaba Cloud Bailian API, especially for Chinese text rendering or photorealistic images
Extract and organize frames from a Bilibili video (bangumi episode, UP upload, or a local file) into scenery shots and per-character image groups, using anime-specific person detection + CCIP character-identity embeddings. Two modes — cluster everyone, or pull out one (or several) named characters via reference folders. Use when the user wants to collect, extract, or organize anime frames/screenshots by character or by scenery from a Bilibili video. Read-only download for personal viewing/analysis; uploads nothing.
Internal helper contract for calling the pi-companion runtime from Claude Code
Internal guidance for composing prompts that Pi runs (DeepSeek by default) handle reliably for coding, review, diagnosis, and research tasks
Internal guidance for presenting Pi helper output back to the user
Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.
Use when the user asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.
Generate Mermaid diagrams (.mmd) and export to PNG/SVG/PDF using mmdc CLI or Kroki API. USE THIS SKILL when user mentions diagram, flowchart, sequence diagram, class diagram, ER diagram, state machine, architecture, visualize, git graph, 画图, 架构图, 流程图, 时序图. PROACTIVELY USE when explaining ANY system with 3+ components, API flows, authentication sequences, class hierarchies, database schemas, or state machines. Supports 11+ diagram types with fully automatic layout.