Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Manage CloudRobo embodied-agent task dispatch (robo-dispatcher) — create embodied tasks that drive a robot via an exec/model and constraints, list/show tasks in a session, cancel tasks, and retrieve task results. Dispatch orchestrates robots (robot_id from cloudrobo-robot) with inference models (exec_model_id from cloudrobo-infer / cloudrobo-asset) inside a session. Triggers include: dispatch, dispatcher, task dispatch, embodied task, agent task, run task on robot, task scheduling, cancel task, task result, robo-dispatcher, 调度, 智能体调度, 任务下发, 机器人任务, 取消任务, 任务结果, 会话任务.
Hunt planted webshells and backdoors across a web source tree — PHP first (also JSP, ASP, Node) — triaging a directory at scale, statically decoding obfuscation layers without ever executing the payload, finding append-infections and fake plugins, and treating known shell families as leads rather than verdicts. Use when a web server is suspected compromised, cleaning a hacked WordPress/Magento/CMS site, vetting a downloaded PHP codebase or plugin for hidden malicious code, or when a file contains eval on decoded input.
Read marked IELTS Writing feedback in a practice vault and produce a periodic progress report with band trends, recurring errors, revision gains, next priorities, and spaced re-probes of older errors. Use whenever the user asks to "summarise my IELTS progress", "how am I doing", "write a progress report", "track my band scores over time", "what errors keep coming up", "are my essays improving", "review an old error", or requests a monthly/weekly writing report. Also use when the user answers a re-probe recorded in `_dashboard/ielts-reprobe-ledger.yaml`. Read existing feedback; do NOT mark new drafts — use ielts-writing-task1 or ielts-writing-task2. Never invent bands for unmarked attempts and never let recent errors crowd older due errors out of review.
Author an IndyKite ContX IQ (CIQ) policy plus its Knowledge Query that sets one or more properties on an existing node in the IndyKite Graph (IKG), then run it via `POST /contx-iq/v1/execute`. Use when adding a brand-new property, overwriting an existing one, or attaching property metadata - no node creation, no relationship writes, no deletes.
Author an IndyKite ContX IQ (CIQ) policy and its Knowledge Query to set one or more properties on an existing relationship in the IndyKite Graph (IKG), then run it via `POST /contx-iq/v1/execute`. Use when adding a brand-new property or overwriting an existing one on a relationship that's already in the IKG. No relationship creation, node writes, deletes, or property metadata (relationship properties take none; metadata on node properties is indykite-ciq-add-property)
Author an IndyKite ContX IQ (CIQ) policy plus its Knowledge Query that creates a brand-new node AND links it to one or more existing nodes via new relationships in a single `POST /contx-iq/v1/execute` call. Use when ingesting a new entity that must be wired into the IKG atomically — combines node creation and relationship creation in one operation.
Author an IndyKite ContX IQ (CIQ) policy plus its Knowledge Query that deletes a node, a relationship, or one or more properties from the IndyKite Graph (IKG), then run it via `POST /contx-iq/v1/execute`. Use when removing data through CIQ — three modes (whole node, whole relationship, individual property) sharing the same policy/KQ shape.
Query InterPro REST API for protein domain architecture, family classification, and member-DB integration. Search entries, retrieve a protein's domains, list family members, get taxonomic distribution, link to PDB. Unifies Pfam, PANTHER, PIRSF, PRINTS, PROSITE, SMART, CDD, NCBIfam. Use uniprot-protein-database for sequences; pdb-database for 3D structures.
Investigates server/infrastructure metric anomalies in PostHog Metrics — from "this metric is rising/dropping/spiking" or a fired alert to a probable cause with evidence. Use when asked why a metric looks wrong (ingestion lag rising, error rate spiking, latency degrading, queue depth growing, throughput dropping), when an alert fires on an OTel/Prometheus metric, or for any incident triage that starts from a metric symptom. Composes characterize-metric-anomaly, query-metrics, and metric-names-list with logs (query-logs) and traces (APM span tools) for cross-signal root-cause correlation.
Senior Java & Spring Boot 4 / Spring Framework 7 architect skill for 2026-standard development. Use when the user asks to build, scaffold, design, review, or explain Java applications using Spring Boot 4.x, Spring Framework 7.x, Spring Modulith, or any related Spring ecosystem project. Triggers include: creating REST APIs, designing microservices, configuring data access (JdbcClient, JPA 3.2, R2DBC), reactive programming (WebFlux), security (Spring Security 7), observability, GraalVM native images, Gradle/Maven build configuration, Jakarta EE 11 migration, and any task requiring idiomatic modern Java (Java 25: records, sealed classes, structured concurrency, scoped values, pattern matching, JSpecify null safety).
Fetches the ranking of trending articles on Juejin, and supports querying the article category list and trending articles by category. Use this skill when the user wants to see Juejin's technical article rankings or get trending articles in areas like frontend/backend/AI.
Review dead letter queue implementations for completeness using the Lenses MCP server. Checks DLQ topic existence, configuration, monitoring, metadata preservation, retry logic, reprocessing paths and connector DLQ alignment. Use when user says "review dead letter queues", "check DLQ setup", "DLQ audit" or asks about error handling, message failures or reprocessing. Do NOT use for reprocessing DLQ messages or managing consumer offsets.
Design custom laboratory hardware as parametric build123d models and export fabrication-ready STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.
Dual-renderer animation orchestrator for METHOD_LAB/historical episodes. By default, CODEX_DIRECT production does not use this skill; use it only when the user explicitly requests the legacy AST, a Remotion/HyperFrames comparison, or restoring a historical episode.
Lark video meetings: query meeting records and artifacts (minutes/transcripts/Miaoji), search/upload/download/edit Miaoji, and have bots join meetings; query ongoing meetings and real-time meeting content (speaking/chat/shared documents), answer questions about meetings, and send in-meeting chat messages/reactions. Look up related information using meeting_id, meeting_no, event_id, note_id, minute_token, vc-node-id, or a Miaoji URL. Use lark-calendar for scheduling, availability, and room management.
Build, register, debug, and operate bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP. Use when authoring or deploying Latch workflows, configuring resources or interfaces, moving data, integrating Registry, or launching and monitoring runs.
Create learning materials, explain concepts, generate quizzes and study aids. Use when asked to explain topics, create tutorials, generate practice questions, make flashcards, design curricula, or help study. Triggers include "explain this", "help me learn", "create a quiz", "tutorial for", "study guide", "how does X work", "teach me", "practice questions".
Transform lecture materials (slides, PDFs, text snippets, transcripts, audio, or video recordings) into comprehensive, exam-ready Markdown notes for Obsidian. Use when the user provides lecture content, study materials, or asks to take notes, summarize lectures, or create study guides. Outputs structured notes with key concepts, definitions, LaTeX math, and exam-important callouts.
Migrates deprecated Letta Filesystem folders/files to MemFS using markdown document corpora, chunking, local lexical search, and QMD semantic search via the memfs-search skill. Use when replacing folders.files.upload, working with PDFs or document QA, or emulating open_file, grep_file, and search_file behavior.
Draft, version, and review a privacy policy compliant with LGPD Art. 9 (seven mandatory elements), Resolução CD/ANPD nº 18/2024 (DPO disclosure) or ATPP channel, international transfer transparency (Res. 19/2024 and Res. 32/2026), and ECA Digital when applicable. Run AFTER consolidating ROPA so the notice matches real data flows. CHECKPOINT skill — requires legal review before publication.
Use this skill when the user says "generate a script", "write a video", "write a long article", "generate a short video script", or "help me write this episode". Based on the practitioner equal-dialogue style (authenticity 9/10, actionability 9/10), first run a content pre-check (goal + cognitive gap), then generate the complete script (with visual annotations) and save it in standard md format, and finally route to li-opening or li-cover. Should not trigger: optimizing only the opening (use li-opening), generating only a cover (use li-cover), or topic analysis (use li-topic). Use when the user wants to "generate script", "write video", "write article", "write long-form content", or needs a full video script or article in the practitioner equal-dialogue style.
Build, read, validate, modify SBML biological network models via the libSBML Python API. SBML Levels 1–3, reactions/kinetic laws, species, rules, FBC extension for flux balance, conversion. Interoperates with COBRApy, Tellurium/RoadRunner, COPASI. Use when programmatically constructing ODE or constraint-based metabolic/signaling models in SBML.
Linear issue tracking and project management through the CLI or GraphQL API. Use when developers mention: (1) Linear issues or tickets, (2) issue tracking or task management, (3) WDY team issues, (4) closing, updating, or triaging tickets, (5) linking PRs to issues, (6) issue states (triage, backlog, started, completed).
Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).
Poisson-model peak caller for ChIP-seq/ATAC-seq BAMs. MACS3 callpeak finds enriched regions (TF sites or histone marks) vs input/IgG; outputs BED narrowPeak/broadPeak for motif analysis, annotation, and differential binding. Use narrow peaks for TF ChIP-seq and ATAC-seq; broad for H3K27me3, H3K9me3, and other broad marks.
Create and manage PostHog reminders — private, human-paced nudges that fire as in-app notifications on a schedule, optionally linked to a PostHog resource. Use when the user says "remind me to…", wants a one-off or recurring nudge (daily/weekly/monthly/yearly, a cron schedule, or a specific date/time), wants to be reminded to look at a dashboard, insight, experiment, feature flag, survey, notebook, replay, or error, or wants to list, change, or cancel their reminders. Covers when to pick a reminder over an alert or subscription, the one-off vs recurring vs cron schedule field mappings, timezones, and attaching a resource.
Install, find, update, and manage agent skills. Use when the user wants to add a new skill, search for skills that do something, check if skills are up to date, or update existing skills. Triggers on: install skill, add skill, get skill, find skill, search skill, update skill, check skills, list skills.
Process, clean, compare, and search tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or Rotman lens. Invoke BEFORE writing code — class names and design() availability vary per coupler type. SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), building custom non-catalog geometry (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), cascading multiple components (use matlab-integrate-pcb-circuit).
Guide for theming .NET MAUI apps—light/dark mode support, AppThemeBinding, dynamic resources, ResourceDictionary theme switching, and system theme detection. USE FOR: "dark mode", "light mode", "theming", "AppThemeBinding", "theme switching", "ResourceDictionary theme", "dynamic resources", "system theme detection", "color scheme", "app theme". DO NOT USE FOR: localization or language switching (use maui-localization), accessibility visual adjustments (use maui-accessibility), or app icons (use maui-app-icons-splash).
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 to creating and managing Model Context Protocol (MCP) servers. How to add custom tools. When to use: (1) when you want to add custom tools to Claude Code, (2) when integrating external services, (3) when you want to build project-specific automation tools, (4) when you want to know how to configure an MCP server. Trigger examples: "create an MCP server", "add a custom tool", "MCP config", "turn an external API into a tool", "test runner MCP".
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.