Skills
100,928 packaged capabilities and playbooks for agents. Install any of them with one command.
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Draft and fill data privacy contract and agreement templates — DPA, data processing contract, GDPR, HIPAA BAA, business associate agreement, AI addendum. Produces signable DOCX files from Common Paper standard forms. Use when user says "DPA," "data processing agreement," "HIPAA BAA," "business associate agreement," or "AI addendum." To understand a U.S. state's consumer privacy law (CCPA etc.) rather than draft, see data-privacy-law-explainer. Includes lawyer-reviewed practice guides; see openagreements.org/editors.
A skill for deciding DB table and column names based on the concepts, entities, and relationships being persisted rather than processing purposes. Use when naming databases, schemas, names related to normalization, or when avoiding names overfitted to a specific use case.
Entry point for Datadog onboarding. Takes a developer's plain-language goal, ensures a valid Datadog account with dd-account-setup, asks dd-product-recommender which products fit, detects the project's platform and cloud, then composes an ordered plan across the existing skills (agent install, product enable, verify, and optional cloud integration) and dispatches to each by source URL — honestly flagging products with no skill yet. Use when the user says "set up Datadog", "onboard my app / this repo to Datadog", "instrument my project", or states a monitoring goal without naming a specific product or skill.
Debug and support PostHog Experiments (A/B tests) for a customer looking at their own results. Use whenever an experiment support ticket is pasted or a customer asks a results question, most commonly "why aren't my exposures even?", "why is one variant getting no traffic?", "why am I missing / seeing too few exposures?", "why does the bias banner show?", or "why don't PostHog's numbers match my SQL?". Pulls the experiment's real data read-only, matches it to a known-cause catalog, and produces a customer-facing explanation, fix, and review of the pertinent numbers. Loads diagnosing-experiment-health as its deep diagnostic library. DO NOT TRIGGER when: creating an experiment (use creating-experiments), only configuring rollout (configuring-experiment-rollout) or metrics (configuring-experiment-analytics), asking lifecycle questions (managing-experiment-lifecycle), or the underlying feature flag is what's misbehaving rather than the results (use debugging-feature-flags).
Researches a topic using parallel web search agents, then creates or updates a structured markdown playbook with sourced practitioner insights. Auto-invoke when user says "deep research", "research playbook", "create a playbook about", "update playbook", or asks to deeply research a topic and write findings into a document. Do NOT invoke for simple web searches, quick questions, or general research that does not produce a persistent playbook file.
Triage playbook for when cold email deliverability breaks. Decision-tree guidance for "I landed in spam", "bounce rate spiked", "domain blacklisted", "inbox blocked in warmup", "reply rate dropped". Tells you what to check first, what to fix, and how long the fix takes. Pair with /email-deliverability-audit for diagnosis.
[Hyper] Use this skill when a build, CI job, or deployment fails with a concrete error and the user asks to diagnose and fix it, including one failing workspace in a monorepo. Do not use it to run a healthy deployment, fix ordinary runtime bugs, design new pipelines, or perform speculative cleanup.
Deploys and monitors ransomware canary files using Python's watchdog library, placing decoy files mimicking high-value targets (financial records, credentials, database exports) where ransomware enumerates first, and alerting via email, Slack, or syslog on any read/modify/rename/delete. Use for early-warning ransomware detection on file servers, NAS, or endpoints, or to supplement EDR where agents can't be deployed.
Identify missing skills and recommend installations from AI Cortex or public skill catalogs. Core goal - provide top 1-3 skill matches with install commands for Agent capability gaps. Use when discovering capabilities or suggesting skills to fill gaps.
Validate that claims in documentation match codebase reality. Extracts verifiable assertions (file paths, commands, function references, behavioral claims, dependencies) from markdown docs and checks them against the actual project. Use after code changes, before releases, or when docs feel untrustworthy.
Create a Technical Specification (SPEC) - Layer 6 of the SDD flow, defining component interfaces, data models, and behavior contracts. Use when ADR decisions are settled and you need an implementation-ready spec before TDD. Single-document authoring primitive; for end-to-end or batch generation the autopilot (`doc-spec-autopilot`) drives this skill.
Validate the SDD corpus - cross-document references, orphans, cumulative-tag gaps, duplicate IDs, and full bidirectional traceability (with optional repair), plus a prose/terminology pass. Use before releases, after batch generation, or to validate and repair the corpus.
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. Use when working with professional documents (.docx files) for creating new documents, modifying or editing content, working with tracked changes, adding comments, or any other document tasks. Do NOT use for plain-text Markdown drafting, PDF work (use pdf-extract or pdf-processing-pro), or rich rendered email/WhatsApp drafts (use the message plugin).
This skill should be used whenever domain modeling is taking place. It provides specialized guidance for type-driven and data-driven design based on Rich Hickey and Scott Wlaschin's principles. The skill helps contextualize current modeling within the existing domain model, identifies inconsistencies, builds ubiquitous language, and creates visualizations (Mermaid, Graphviz/DOT, ASCII diagrams) to communicate domain concepts clearly. Use this skill when designing types, modeling business domains, refactoring domain logic, or ensuring domain consistency across a codebase.
Generates Minimal API endpoints following Microsoft's recommended approach. Creates fast, testable HTTP APIs with minimal code using MapGet/MapPost/MapPut/MapDelete. Preferred over controller-based APIs for new projects.
Teach the user a topic as an adaptive tutor — retrieval practice, spaced repetition with decay, and persistent memory in ~/.drill-me/. Use when the user wants to learn or be drilled on something, says "drill me on X", "teach me X", "quiz me on X", or wants to study or revise a topic, a codebase, or a document.
Deploys an application to Embarko, a managed hosting environment that builds your app automatically (no Dockerfile required) and makes it reachable at a generated URL. Use this whenever the user asks to deploy, redeploy, ship, push, or release an app, to make a deployed app do something on a timer (daily report, nightly clean-up), to change who is alerted when a deployed app goes down (email, Slack, webhook, phone), to store files for an app (user uploads, images, PDFs, a public link to a file), or to showcase / feature / list a deployed app on an Embarko showcase page (public or event).
Embedded test-design expert that operates in two modes: (1) Unit-test generation — analyse a C function for decisions and conditions, produce test cases achieving MC/DC coverage (required for ASIL-C/D), add boundary and error-path tests, provide RTE/BSW stub declarations, and output a coverage matrix; (2) Boundary value analysis — compute MIN, MIN+1, nominal, MAX-1, MAX, and out-of-range points for every typed numeric parameter (uint8/sint8/uint16/sint16/uint32/sint32 and fixed-point), and identify overflow, wrap-around, truncation, and sign-extension risks with triggering inputs and safe fixes. Test output is compatible with Unity, CppUTest, and VectorCAST patterns. A third use, characterization testing, pins the existing behaviour of legacy code before a modernization step so equivalence can be proven after the change. Returns decision-ready, self-checked test sets with explicit coverage gaps stated.
Analyze, manipulate, compare, annotate, and visualize phylogenetic or other hierarchical trees with ETE 4. Use for Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy, SmartView exploration, and publication rendering. Do not use it to infer trees from raw sequences; align sequences and infer a tree first.
Entry point for the CodeStable skill engineering loop. Triggers: writing or modifying a cs skill, evaluating skill effectiveness, quantifying across models/agents, optimizing skill prompts, or consolidating conclusions back into a skill. Internally drives author, eval, optimize, release.
Framework for running single-variable cold email experiments. Defines experiment types (list-only, copy-only, combined), confidence weighting, minimum sample sizes, and success criteria. Use when the user wants to improve a campaign, test a new list vs old one, or compare copy variants. Prevents the #1 learning-loop mistake — changing list + copy + offer at once and losing all signal.
Use when an approved PR head must reach production through a gated release — exact-head merge, staged canary rollout with threshold verdicts, and a SemVer-tagged release with notes plus a monitor handoff. Triggers on post-merge rollout work; not for continuous monitoring, review depth, or infra provisioning
Read and modify GrowthBook feature flags — create, search, toggle, target, schedule, ramp, monitor, publish drafts, and archive. Use when the user mentions a feature flag, feature toggle, kill switch, rollout, targeting rule, percentage release, saved group, prerequisite, draft revision, flag approval, or flag cleanup. Triggers include "create a flag for X", "release this to 10% of users", "turn on flag X in production", "gradually roll this out", "publish this draft", "what flags do we have", "who needs to approve this", and "delete this stale flag". For designing, launching, analyzing, or stopping an A/B test, use the experiments skill. For charting product data or browsing the metric catalog, use the analytics skill. For first-time API key configuration, use gb-setup.
Dual-mode Twitter/X writing tool. Mode 1: input a Twitter account, auto-fetch popular tweets and extract a writing style DNA document. Mode 2: based on style DNA and a topic, compose high-quality tweets, threads, or X long-form posts. Use when users want to analyze Twitter style, extract writing style, write tweets, write threads, imitate someone's tweet style, or ghostwrite tweets.
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.