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Found 2,408 Skills
Interactive Pinecone quickstart for new developers. Choose between two paths - Database (create an integrated index, upsert data, and query using Pinecone MCP + Python) or Assistant (create a Pinecone Assistant for document Q&A). Use when a user wants to get started with Pinecone for the first time or wants a guided tour of Pinecone's tools.
Tests Amazon MWAA workflow execution end-to-end: trigger a run and monitor it to completion for Provisioned (Python DAG, via Airflow REST API) and Serverless (YAML workflow, via StartWorkflowRun). Verifies the artifact is deployed and parse-ready, triggers with confirmation, polls to terminal state, and on failure delegates diagnosis to debugging-mwaa-workflow and artifact/redeploy fixes to authoring-mwaa-workflow, then retests up to a capped number of attempts. Triggers on: test my DAG, test my workflow, run my DAG, trigger a test run, does my DAG work, smoke-test the pipeline, verify my workflow runs, execute my DAG to check it. Not applicable to writing or deploying a new workflow (handled by authoring-mwaa-workflow), or for diagnosing why a run failed or root-causing an error (handled by debugging-mwaa-workflow).
Build on ZooWork Managed Agents through the `@zoowork-ai/sdk` TypeScript SDK or `zoowork` Python SDK. Use whenever ZooWork, a `zwp_live_`, `agt_`, or `skl_` identifier, `ZOOWORK_API_KEY`, a ZooWork Agent or Session, streaming events, custom tools, MCP, platform Skills, Environments, channels, schedules, approvals, or ZooWork API errors are mentioned. Inspect the installed SDK version and read the routed reference before writing ZooWork code.
Animation in Blender 5.2 - slotted/layered actions and the channelbag API, Python keyframing, F-curves, game loops, NLA clips, pose library, mocap/BVH retargeting via constraints, baking control rigs to export skeletons, root motion, per-clip export. Use for any keyframe, action, NLA, mocap, or animation-export task.
Create and edit native editable PPTX decks with the local xdoc CLI. When the user wants to create, build, generate, modify, edit, refactor, rebrand, or fill a PowerPoint deck / slides / presentation / .pptx, including: 创建 PPT / 做 PPT / 生成演示文稿 / 修改 PPTX / 改一下幻灯片 / 快速做一份 / 一句话生成 / 帮我快速出一版 / 简单提示词生成 / quick deck / reference deck style matching with a new outline, data-driven decks, brand checks, applying a corporate rebrand, creating or safely editing PPTX animations/transitions, exporting PDF/PNG previews. Also use for xdoc Runtime license installation, renewal, activation, and authorization diagnostics for pptx-nova. Triggers on .pptx filenames, words like deck/slides/presentation/PPT/幻灯片/演示文稿, or any request that ends in "a PowerPoint file". Prefer this skill over hand-writing python-pptx / PptxGenJS / SVG-to-PPTX pipelines — xdoc CLI produces natively editable PPTX with dry-run, sidecar replay, and structured error self-repair.
Python Optimization Modeling Objects. A high-level framework for formulating, solving, and analyzing optimization models. Supports Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Non-Linear Programming (NLP). Part of the COIN-OR project. Use for mathematical optimization, linear programming, mixed-integer programming, non-linear programming, strategic planning, process engineering, energy systems, supply chain optimization, stochastic programming, and solver integration with IPOPT, SCIP, Gurobi, CPLEX, or GLPK.
Sets up CloudWatch Application Observability (also called Omni) for the first time. Covers creating an Omni Space or Domain; configuring and listing Omni access grants (who has access and at what level) and access profiles bounding what async alerts, integrations, or agents can do; instrumenting an application or AI agent with the ADOT SDK so traces reach CloudWatch Omni (Python/Node/Java/.NET on EC2/ECS/EKS/Lambda) — CloudWatch Omni only; for Application Signals (auto-instrumentation, monitored service, ServiceEvents, reporting telemetry) use aws-observability — including no-image-rebuild and .NET CoreCLR profiler env vars; ingesting Azure telemetry via the CloudWatch agent on an Azure VM or AKS cluster; connecting Slack to a Space (and whether GitHub can be connected); and registering a custom MCP tool server over HTTP or stdio and choosing its auth (API key, bearer, or OAuth2). For using a Space already set up — querying, dashboards, Omni alerts, or defining Omni resources as code — use aws-observability.
Migrate Python Agno applications to Pydantic AI and, only when needed, Pydantic AI Harness. Use when source code imports `agno` or relies on Agno agents, teams, workflows, sessions, memory, knowledge, tools, hooks, guardrails, approvals, skills, streaming, or AgentOS.
Onboard prek (Rust-powered pre-commit) into any project and suggest hooks tailored to the language/framework. Use when the user says "add prek", "set up pre-commit hooks", "configure prek", "what hooks should I use", or when you notice a project without a prek.toml that would benefit from pre-commit checks. Also trigger when the user wants to add new hooks to an existing prek.toml, audit their hook config, or migrate from pre-commit to prek. Covers Rust, Python, TypeScript/JavaScript, Go, Ruby, and Shell projects. Do NOT use for husky, lint-staged, or CI pipeline hook configuration — this skill is specifically for prek.
Builds, versions, publishes, tests, and executes Google Cloud Application Integration workflows through the REST API and Python discovery client, and promotes versions across environments. Use when listing integrations, downloading or uploading integration versions as JSON, configuring API triggers or config variables, publishing drafts, invoking integrations, or automating CI/CD promotion. Do not use for initial region provisioning and IAM setup (use application-integration-basics) or diagnosing failed runs and logs (use application-integration-troubleshooting).
Compares an app clone against the original: a feature parity score from the feature matrix (weighted by must, should, could) with the missing list in build order, plus a screenshot layout diff that ignores colour so a rebrand does not count against you. Two standard-library Python tools. Use when the user says "how close is my clone", "compare it to the original", "what's missing", "parity check", "diff the screens", "is it ready", or after /replica-test.
Comprehensive methodology for auditing and exploiting TLS/SSL implementations and misconfigurations across network services and mobile applications. Covers protocol downgrade attacks including POODLE (CVE-2014-3566) against SSLv3 CBC padding, DROWN (CVE-2016-0800) cross-protocol attack leveraging SSLv2 export ciphers to decrypt TLS sessions, and FREAK (CVE-2015-0204) forcing RSA export-grade key exchange. Addresses BEAST (CVE-2011-3389) exploiting CBC IV predictability in TLS 1.0, CRIME (CVE-2012-4929) and BREACH targeting TLS-level and HTTP-level compression oracles respectively, and Heartbleed (CVE-2014-0160) for OpenSSL memory disclosure. Covers certificate validation bypass techniques for applications with improper hostname verification or chain validation, certificate pinning bypass using Frida and Objection for mobile application interception, HSTS bypass via NTP manipulation and subdomain exploitation, TLS 1.3 0-RTT replay attacks against non-idempotent endpoints, mutual TLS (mTLS) authentication attacks including client certificate theft and relay, and Certificate Transparency log monitoring for reconnaissance. Primary tooling includes testssl.sh for comprehensive TLS auditing, sslyze for Python-integrated scanning, sslscan for quick cipher enumeration, and tlsx for high-speed TLS probing at scale. Maps to CWE-295 (Improper Certificate Validation), CWE-319 (Cleartext Transmission of Sensitive Information), and CWE-757 (Selection of Less-Secure Algorithm During Negotiation).