Top Agent Skills

Generate a conference poster (article + tcbposter LaTeX → A0/A1 PDF + editable PPTX + SVG) from a compiled paper. Use when user says "做海报", "制作海报", "conference poster", "make poster", "生成poster", "poster session", or wants to create a poster for a conference presentation.

Send notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.

Export Marp slide markdown files to PDF (default), HTML, PPTX, or PNG. Handles theme loading, Chrome/Chromium detection for PDF export, and batch conversion. Trigger when user says "export slides", "convert marp to pdf", "marp export", "slides to pdf", "slides to html", "导出slides", "slides转pdf", "导出演示文稿".

Unified Agent Teams orchestrator for Diverga v12.0.0. Manages Agent Teams creation, VS Arena debate, and subagent dispatch. Single entry point for all parallel/debate workflows. Replaces research-orchestrator and vs-arena skills. Triggers: orchestrator, agent team, create team, parallel agents, debate, competing, collaborate, VS Arena

Periodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.

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

Get a deep critical review of research from GPT via Codex MCP. Use when user says "review my research", "help me review", "get external review", or wants critical feedback on research ideas, papers, or experimental results.

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when user says "实现实验", "implement experiments", "bridge", "从计划到跑实验", "deploy the plan", or has an experiment plan ready to execute.

Defamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.

Structures and derives research formulas when the user wants to 推导公式, build a theory line, organize assumptions, turn scattered equations into a coherent derivation, or rewrite theory notes into a paper-ready formula document. Use when the derivation target is not yet fully fixed, the main object still needs to be chosen, or the user needs a coherent derivation package rather than a finished theorem proof.

Project directory organization and script naming conventions for research

Revise an academic paper based on internal review comments. Reads review report or annotated manuscript, then applies revisions one by one with user approval. Trigger when user says "self revise" / "paper-selfrevise" / "内部修改" / "根据审稿意见修改".

Cleans a Quarto (.qmd) file by replacing LaTeX holdovers with proper Quarto/Pandoc syntax so the document renders correctly to HTML, PDF (Typst/LaTeX), and Word. Fixes citations (\citep → [@key]), cross-references (\ref → @label), figures (\includegraphics → markdown), tables, text formatting (\textbf → **bold**), inline math (\( \) → $ $), hyperlinks (\href → [text](url)), footnotes (\footnote → ^[]), list environments, section headings, and R Markdown chunk options (dot-style → #| YAML). Use when asked to clean, fix, modernize, or port a Quarto or R Markdown document; when LaTeX commands appear in a .qmd file; when a document fails to render to Word or Typst; or when citations/cross-references do not appear in non-LaTeX output.

Turns a rough request into working software via a governed build loop: align first, plan, then iterate one task at a time with deterministic backpressure and holdout-scenario judging.

AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.

Rewrite the previous response more briefly while preserving the substance.

Interact with GitHub issues - create, list, and view issues.

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Compare AI agent-made UI variants locally in a real app, then keep one and clean up unused temporary code.

Audit a component or page for accessibility issues and fix them

Design user flows and navigation structure following proven UX patterns

Conduct a retrospective on a coding session.

Grill me about specs for the workflows I want to build, within this workspace.

Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

Stop. That last message did not land: re-pitch it.

Writing, exploit: shape raw material into an article, paragraph by paragraph.

Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.

Wire dependency-cruiser into a TypeScript repo so each package is a deep module, with implementation hidden in subfolders and reachable only through its entry-point files. User-invoked.

Prüft Bonus-Rabatt-Klauseln in AGBs nach BGB, erstellt Redline, Ersatzfassung und Risikoampel mit Verbraucher-/B2B-Unterscheidung.

Builds distinctive, production-grade frontend interfaces with bold aesthetics, avoiding generic AI design patterns.

Runs OWASP ZAP security scans against web applications using Java or Docker, with setup guidance and links to upstream documentation.

Parses and evaluates Content Security Policy headers using csp-parse and csp-evaluator libraries. Identifies overly permissive directives, missing protections, and generates tightened policy recommendations.

Generates a complete marketing pipeline for apps, dev tools, and SaaS products, including positioning, listing assets, launch plans, and growth strategies, adapting to product type.

Performs a full-stack security posture assessment with 0-100 risk scoring, scanning dependencies, code patterns, configuration, and data handling, then produces a prioritized report and routes to specialized skills.

Queries real-time vulnerability intelligence from NIST NVD, CISA KEV, EPSS, and MITRE ATT&CK via a remote MCP server, offering seven tools for CVE lookup, search, and trending analysis.

Translates text between languages with pronunciation guidance for non-Latin scripts and context notes.

Delegate coding tasks to the OpenCode CLI, including one-shot runs, interactive sessions, and PR reviews.

Frames release launches by defining messaging, sequencing, channel selection, and rollout logic across product, growth, and support teams.

Make the agent solve coding tasks with the least code that remains correct. Before writing code, walk the Ponytail ladder: skip what need not exist, then prefer stdlib, native platform features, already-installed dependencies, one line, and only then the minimum custom code. Use when the user asks for ponytail mode, less code, YAGNI, anti-bloat, minimal code, an over-engineering review, a current-diff delete-list, a whole-repo bloat audit, or a `ponytail:` tech-debt harvest. Keep validation, data-loss handling, security, and accessibility. Mark shortcuts with `ponytail:` plus the upgrade path. Triggers on: ponytail, /ponytail, /ponytail-review, /ponytail-audit, /ponytail-debt, write less code, YAGNI, over-engineering, anti-bloat, minimal code, do I need this, lazy dev.

Routes a research topic through a structured two-phase workflow: generate an extensible outline, then fan out parallel web-search agents to investigate each item into validated JSON, producing a complete markdown report with table of contents.

DataPerf: Benchmarks for Data-Centric AI Development

Structure a hard business decision — frame the choice, score options against weighted criteria, run a pre-mortem and stress-test, and produce a recommendation + decision record for any active brand

Rust testing patterns including unit tests, integration tests, async testing, property-based testing, mocking, and coverage. Follows TDD methodology.

Data Analyst IA — Expert en analyse de données (SQL, BI dashboards, Metabase, Superset, reporting, KPIs)

Use when data management, data governance, data quality assurance, or data lifecycle management is needed. This agent specializes in data management within the ExecForge AI ecosystem.

Drafts U.S. internal legal memoranda using IRAC structure to analyze issues, synthesize authority, assess risks, and recommend strategy. Use when asked to draft a research memo, internal memo, issue analysis, case strategy memo, or any IRAC-based legal analysis.

Drafts structured client memoranda translating legal analysis and strategic recommendations into plain language for non-lawyer audiences. Covers corporate governance, fiduciary duties, compliance, and transactional advice. Enforces standard memo architecture: heading block, executive summary, background, analysis, options, and recommendations. Use when preparing client-facing memos, opinion letters, or governance briefings.

WordPress Consultant

Conduct gap analyses between current and desired states. TRIGGERS - Use when user needs help with gap-analysis related tasks.

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.

AI 3D model generation agent. Generates text-to-3D and image-to-3D code (Python/JS/OpenSCAD) using Meshy, Tripo, Hunyuan3D, Rodin, Sloyd, and Stability APIs. Handles game pipeline integration, LOD, retopology, UV, and QC validation.

Run a source-grounded paid-advertising audit across major platforms including Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Produces a versioned JSON audit bundle and human-readable reports with platform health scores, evidence coverage, and prioritized actions.

Structure compelling design presentations for stakeholders, reviews, and showcases.

Translates Apple's fluid interface design principles—spring animations, direct manipulation, interruptibility, and velocity handoff—into web implementations using CSS, Pointer Events, and spring libraries like Motion/Framer Motion.

Interact with Xiaohongshu (Little Red Book) posts by posting comments, replying to comments, liking, and favoriting content through a CLI script.

Generates images and conducts conversations through the Gemini website (gemini.google.com) using MCP tools, scripts, or a managed browser as a fallback.

Connects AI coding agents to the IOTA blockchain with tools for wallet management, Move smart contract development, and on-chain data queries via JSON-RPC and GraphQL.

Adopts the perspective of Naval Ravikant to answer questions using his mental models, decision heuristics, and core concepts like leverage, specific knowledge, and desire management.

用 Serenity 的供应链卡点逆向投资逻辑分析美股/AI 供应链标的,产出专业投研报告,包含逆向链显形、卡点判据、估值与证伪门。