Skills
98,873 packaged capabilities and playbooks for agents. Install any of them with one command.
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Assess and classify legal risks using a severity-by-likelihood framework with escalation criteria. Use when evaluating contract risk, assessing deal exposure, classifying issues by severity, or determining whether a matter needs senior counsel or outside legal review.
Legal Visualization. A skill for generating legal diagrams and charts for legal business scenarios; use it when the user asks to organize case materials, contract materials, compliance matters, transaction arrangements, chains of evidence, litigation processes, timelines, legal relationships, client reports, legal service proposals, or lawyer team work into relationship diagrams, flowcharts, timelines, evidence chains, risk maps, roadmaps, PNG/SVG/PDF/.drawio; also compatible with terms such as “法律可视化” (legal visualization), “案件事实图” (case fact diagram), and “法律关系图” (legal relationship diagram). First filter scenarios by audience, task verb, and routing rules, then generate deliverable images and keep the draw.io source file as an editable draft. This skill is not for fact verification and does not replace legal conclusion judgments.
Draft, version, and publish a privacy policy compliant with LGPD Art. 9 (seven mandatory elements) and ECA Digital if minors are present. Use when the user asks “política de privacidade,” “privacy policy,” “termos de uso,” “aviso de privacidade,” or as part of an audit pipeline. Versions every published change. Output goes to `.lgpd/policies/privacy-policy-v{N}.md`. CHECKPOINT skill — never publish without legal review.
Define retention rules and erasure mechanisms (LGPD Arts. 15-16) reconciling subject's right to erasure (Art. 18, VI) with legal retention obligations (fiscal, labor, banking). Use when user asks 'retenção LGPD', 'quanto tempo guardar', 'eliminação de dados', 'soft delete vs hard delete', 'crypto-shredding', 'right to be forgotten'.
Use the [incremental maintenance mode] of this skill when the user says "update the index", "add this to the index", "added a new file", "added a new book/note/document", or "the asset library index needs updating". Use the [health-check mode] of this skill when the user says "index health-check", "check the index", "sync the index", or "fill in missing index entries", scanning all libraries ↔ INDEX to find missing/invalid entries and fill them in in bulk. Applies to all libraries with an INDEX.md: reading-note libraries, core-concept libraries, viral-script libraries, 04-方法论沉淀, and any libraries created in the future. The value of an index depends on content accuracy — you must read the original text in full before writing; inferring from file names or impressions makes the index lose its reference value. Even if the user only says "I added a file" or "put this in", trigger this skill as long as an index is involved. Do not trigger for: merely consulting the index (Read directly), deepening topic selection (use li-topic), generating scripts (use li-writer).
Reviews, curates, and maintains the Forge library of agents, skills, and templates. Performs deduplication analysis, staleness detection, quality promotion, and orphan reference checking. Produces structured review reports with actionable recommendations for merging, archiving, or promoting library items. Use this skill when the user wants to review the library, clean up agents or skills, check what's available, find duplicates, trim unused items, see library statistics, or says "what's in my library?" Also triggers on scheduled review intervals or when the library grows beyond 20 items. Do NOT use for creating new agents (use Agent Creator), creating skills (use Skill Creator), or planning teams (use Mission Planner).
Look up, search, create, and update Linear issues, projects, initiatives, documents, and cycles. Use when working with teams, labels, and comments, with customers, customer requests, and feedback, attaching files, or linking GitHub PRs and issues, GitLab MRs, Slack, or Discord messages to Linear items.
Introduces LinuxMirrors' positioning, capabilities, supported scope, source code and authoritative references, and verifies the official website, GitHub and current source code first when answering about project status, compatibility, script differences, recent changes or sources. Use it to understand the project and choose the right workflow; for hands-on system package source work or changing sources during Docker installation, follow the corresponding dedicated process instead — do not use this skill as a substitute for a change plan.
Plans and guides LinuxMirrors system package source changes for GNU/Linux hosts, covering distribution detection, domestic/education-network/overseas/official sources, interactive and unattended parameters, EPEL and EOL scenarios, backup, verification, troubleshooting and rollback. Use when the user explicitly wants to change apt/yum/dnf/pacman/zypper/apk/portage/Nix package sources; for Docker CE and Registry Mirror, use the dedicated Docker process instead.
Transforms any subject knowledge point into a vertical educational infographic (9:16). The user only needs to enter a knowledge point name (such as "sound phenomena," "Pythagorean theorem," "photosynthesis"), and the Skill automatically: identifies the subject/grade/chapter, breaks it down into 3-5 core sub-concepts, assigns a theme color scheme, generates specific illustration descriptions for each sub-concept, builds a complete prompt, and calls linyuebanzi-image-gen to generate the image. Built-in two-layer subject accuracy check: self-check the prompt against a per-subject checklist before generation, then read back the PNG for visual review after generation (text/formulas/diagrams), with automatic retries on failure to ensure the content delivered to students is accurate. Built-in illustration guidance for subjects including physics (sound/light/heat/force/electricity/lenses/mechanical motion), math, chemistry, biology, Chinese, history, and English. Supports batch generation - "all chapters of first-semester 8th grade physics" will be generated chapter by chapter, each with a different color scheme and a consistent style. Trigger words include: make an infographic, knowledge card, subject diagram, physics infographic, chemistry infographic, make a knowledge chart, draw a knowledge card, turn this knowledge point into an image. Do not use for dynamic interactive demos (use the interactive demo Skill), article cover images (use linyuebanzi-cover-generator), or hand-drawn style article illustrations (use linyuebanzi-inline-diagram).
Build targeted company lists for outbound campaigns using Extruct. Use when the user wants to: (1) find companies matching an ICP, (2) build a prospect or outbound list, (3) search for companies by description, (4) discover companies in a market segment, (5) create a target account list, (6) research a competitive landscape, (7) find lookalike companies from a seed list. Triggers on: "find companies", "build a list", "company search", "prospect list", "target accounts", "outbound list", "discover companies", "ICP search", "lookalike search", "seed company".
Add research-powered enrichment columns to Extruct company tables. Use when the user wants to add enrichment columns (e.g. funding, verticals, tech stack) to an existing Extruct table, run column configs from enrichment-design, or monitor enrichment progress. Triggers on: "enrich", "add column", "add data point", "research column", "enrich table", "enrichment", "add a field", "run enrichment", "monitor enrichment".
Literary ghostwriter skill that mimics the writing style of seven literary masters for creative writing. Extended with long-form novel project management, multi-role writing workflow, and consistency tracking. Triggers when: Writing in a specific author's style, creative writing, script writing, novel writing, long-form fiction planning, chapter continuation, or style imitation exercises. Commands: - /文豪 <作家> <选题> — Single-shot style imitation (7 authors) - /literary <author> <topic> — English single-shot style imitation - /文豪 迁移 <源→目标> <文本> — Style transfer: re-voice existing text into another author's style - /文豪 迁移 校核 <文本> <目标作家> — Verify a transfer against its source - /文豪 迁移 矩阵 — Show the inter-author transfer matrix - /literary transfer <src->target> <text> — English style transfer - /文豪 新建 <项目名> — Create novel project with world-building - /文豪 打开 <项目名> — Open existing project - /文豪 项目 — Show project status - /文豪 规划 — Analyze novel position, plan next moves - /文豪 大纲 [操作] — Generate/modify plot outline - /文豪 章纲 <章节号> — Generate chapter-level outline - /文豪 设定 <世界观元素> — View/modify world-building - /文豪 人物 [角色名] — View/modify character card - /文豪 伏笔 — View foreshadowing tracker - /文豪 续写 — Smart continuation from current position - /文豪 润色 <文本> — Style optimization - /文豪 审稿 [章节] — Editor review - /文豪 去AI味 <文本> — AI-trace reduction - /文豪 回收站 — Recycle bin for deleted content Capabilities: Deep analysis of author's spiritual core, providing concrete methods for authentic imitation, bilingual Chinese-English creation, multiple genre support, inter-author style transfer with four-layer re-voicing and plot-preserving constraints, long-form novel project management, multi-role writing workflow (planner/character-dev/stylist/editor), consistency tracking, chapter-by-chapter smart continuation, foreshadowing management.
Design and audit live event operations for mobile games, PC games, apps, SaaS communities, marketplaces, launches, seasonal campaigns, limited-time offers, reward calendars, challenges, tournaments, content drops, promotions, and lifecycle events. Use when planning event calendars, segmentation, eligibility, economy impact, rollout, observability, support, compensation, rollback, or post-event learning.
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, Intellect 3. One API for all models with automatic fallback and cost optimization. Use for: AI assistants, code generation, reasoning, agents, chat, content generation. Triggers: claude api, openrouter, llm api, claude sonnet, claude opus, gemini api, kimi, language model, gpt alternative, anthropic api, ai model api, llm access, chat api, claude alternative, openai alternative
Local resource library navigation — the structure and usage of the dictionary library (Dic), payload library, and POC library. Essential reading when you need directory brute-forcing with ffuf/spray, password brute-forcing, or building fuzz payloads. Covers dictionary selection strategy, payload template invocation, and POC library search methods. The dictionary library is installed uniformly under /pentest
Logo design principles and AI image generation best practices for creating logos. Covers logo types, prompting techniques, scalability rules, and iteration workflows. Use for: brand identity, startup logos, app icons, favicons, logo concepts. Triggers: logo design, create logo, brand logo, logo generation, ai logo, logo maker, icon design, brand mark, logo concept, startup logo, app icon logo
Implement-review-fix loop for development tasks. Use when the user invokes $loop, says "loop", "loop this", "run the loop", "implement then review", "review/fix until clean", or otherwise asks Codex to keep cycling through implementation, review, fixes, and re-review until no actionable issues remain.
Professional contract analysis, review, annotation, and redlining. Use when the user asks to review contracts, agreements, clauses, NDAs, procurement or service contracts, SaaS or data agreements, employment or consulting agreements, IP licenses, or financing documents, or requests risk analysis, clause-by-clause annotation, track changes, negotiation advice, or review reports; supports in-place comments and track changes for DOCX, and located review of PDFs, images, or plain text.
Top-level Lytics CDP agent - routes user intent to the appropriate skill for audience management, profile exploration, data integration, and schema browsing. Use when the user has a general Lytics question or request that doesn't clearly map to a specific skill.
Use when creating Makefiles for process lifecycle management with PID tracking, logging, and status monitoring. Triggers on: 'use makefile mode', 'makefile', 'create makefile', 'process management', 'background jobs', 'start/stop services'. Full access mode - can create/modify Makefiles.
Help developers integrate Apple MapKit into iOS/macOS apps. Use this skill when users ask to add a map to their app, display maps, show user location on a map, add markers/pins/annotations, implement map clustering, get directions/routing between locations, search for places/points of interest, implement MapKit features, work with MKMapView, SwiftUI Map, MKAnnotation, MKOverlay, MKDirections, MKLocalSearch, or any MapKit-related development task.
Terrain and hillshade in MapLibre GL JS — raster-dem sources, Terrarium vs. Mapbox RGB encoding, hillshade layer configuration (single and multi-pass), 3D terrain, dynamic contour lines, and self-hosting DEM tiles. Use when adding elevation context, hillshade, or 3D terrain to a map.
Plan manipulator motion and generate trajectories in MATLAB. Use when the task involves moving a robot arm between configurations or poses — whether the user says "trajectory," "motion," "path," "move from A to B," or "plan." This skill applies regardless of whether the user explicitly mentions collisions or obstacles; if geometry exists in the workspace, collision safety is implicit. Triggers on: manipulatorRRT, manipulatorCHOMP, dlCHOMP, contopptraj, trapveltraj, collision-free path, motion planner, RRT, CHOMP, TOPPRA, path shortening, obstacle avoidance for manipulators, time-optimal trajectory, velocity limits, acceleration limits, occupancyMap3D, meshtsdf, collision objects as environment, trajectory between waypoints, joint interpolation, move between poses, constant velocity, trapezoidal profile, feed rate. Also triggers when a user has IK solutions or waypoints and needs to connect them — whether for time-optimal motion, constant-speed welding/cutting, or any other trajectory parameterization.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
mdtraj molecular dynamics trajectory analysis (Python). Reads DCD/XTC/TRR/NetCDF/H5/PDB topologies and trajectories; computes RMSD vs time, radius of gyration, per-residue RMSF, residue-residue contact frequency maps, phi/psi torsions for Ramachandran plots (general + Gly/Pro), and 8-state DSSP secondary structure. Modules: trajectory I/O, geometry (distances/angles/dihedrals), structural analysis (RMSD/Rg/RMSF/SASA), contacts, hydrogen bonds, secondary structure (DSSP), NMR observables. For broader atom-selection grammar use mdanalysis-trajectory; for running MD simulations use OpenMM/GROMACS.
Structure and summarize INTERNAL meeting transcripts (standups, planning, retros, 1:1s) into decisions, owned action items, blockers, sentiment, and a draft follow-up email staged in Gmail. Use when: "analyze this meeting", "extract action items", "meeting minutes", "summarize this standup", "summarize this planning meeting", "retro summary", "follow-up email from these notes", "what did we decide in [meeting]". NOT for sales or prospect calls — route those to call-recording-analyzer-skill (Clari scorecard) or sdr-call-coaching. Wires create_draft for the follow-up email; if the draft would go outside Epiphan, runs it through the brand-voice gate first.
Generate Mermaid diagrams for chatbot flows that render in Markdown, including choosing diagram types, producing valid Mermaid code blocks, and validating or rendering diagrams locally via the bundled scripts. Use when a user asks for chatbot flowcharts/sequence/state diagrams, wants Mermaid syntax, or needs to verify/render Mermaid without a web service.
Apply structured decision analysis using decision matrices, decision trees, expected value, and multi-criteria decision analysis (MCDA). Use this skill when the user faces a complex decision with multiple options and criteria, needs to compare alternatives objectively, quantify risk vs reward, or facilitate group decisions — even if they say 'which option should we choose', 'help me decide', 'how do we compare these options', or 'what's the expected outcome'.
Design production plans using MPS (Master Production Schedule), MRP (Material Requirements Planning), and capacity planning. Use this skill when the user needs to schedule production, plan material procurement, balance capacity with demand, or optimize production sequencing — even if they say 'we can't keep up with orders', 'when should we order materials', 'production scheduling', or 'how do we plan for next quarter's demand'.
Prepare Microsoft Store release readiness for Windows apps, desktop utilities, games, PWAs, and packaged software including package identity, MSIX/AppX packaging, Store listing, screenshots, age ratings, privacy, capabilities, in-app purchases, subscriptions, updates, certification, installer behavior, Windows integration, telemetry, crash quality, support links, and release rollout. Use when submitting or auditing products for Microsoft Store.
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
Guided workflow for taking any ML codebase — including one with no experiment tracking at all, or one full of MLflow 2-era idioms — to a production-grade open-source MLflow 3 setup with dev/staging/prod environments, registry-based promotion, and served models. Walks seven phases with a developer who may have zero MLflow 3 experience — assess the codebase (scripted read-only audit), model the registry domain (per-environment model names, aliases, gates), stand up tracking per environment, restructure training code to MLflow 3 idioms, wire evaluation-gated promotion, serve and smoke-test, then run the ongoing MLOps loop. Use when asked to set up MLflow, migrate to MLflow 3, productionize model training and serving, or design a dev/staging/prod MLOps cycle. Pairs with the sibling mlflow-3 rule pack for every API decision.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.