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Found 9,586 Skills
Printing Press CLI for Pypi. PyPI JSON API. Look up Python package metadata, versions, release files, and vulnerability data. Browse recent...
Interact with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
Writing or debugging tests, choosing unit vs integration style, Postgres/ClickHouse tests, regenerating ClickHouse test schema, or exporting test helpers from packages without pulling test code into production bundles.
紫鸟访问策略管理：网页访问规则、网页/网页分组、规则生效成员/账号、账号绑定策略的查询和维护。当前无快捷命令，全部通过 ziniao-cli api 直调。
创建 ziniao-cli 的自定义 Skill。当用户需要把紫鸟 API 操作封装成可复用的 Skill（包装原子 API 或编排多步流程）时使用。
Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.
Delegate a coding task to the OpenAI Codex CLI as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Codex — phrasings like "have Codex do X", "delegate this to Codex", "run it through Codex", or "use Codex to implement/fix/refactor" — or wants to run a queue of coding tasks through Codex while staying the reviewer. Prefer it over a one-shot Codex forwarder (such as the codex-rescue agent) specifically when the user will review the resulting diff and commit it themselves, or wants the full brief → dispatch → review → commit loop across a single task or a queue. Also reach for it proactively for a separate implementation pass on a bounded, well-specified task (an implementation sweep, a migration, a mechanical refactor, parallel work). Covers writing the Codex brief, dispatching it via the bundled relay.mjs helper, waiting for completion, reviewing the result, and committing. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.
Hugging Face CLI to estimate the required memory to load Safetensors or GGUF model weights for inference from the Hugging Face Hub
Manage DNS records on DNSPod (Tencent Cloud's DNS service). Use when the user asks to add / update / delete A / AAAA / CNAME / MX / TXT / NS / SRV / CAA records, list records for a domain, search records, add ACME challenge / SPF / DKIM / domain-verification TXT records. Backed by the official tencentcloud-sdk-python DNSPod client.
EAS service (paid). Use for anything related to EAS Observe - adding `expo-observe` to an Expo project (AppMetricsRoot/ObserveRoot HOC, markInteractive, the useObserve hook, the Expo Router / React Navigation integrations for per-route metrics, and user-defined events via `Observe.logEvent`), querying via the EAS CLI (`eas observe:metrics-summary`, `observe:metrics`, `observe:routes`, `observe:events`, `observe:versions`), or interpreting the resulting metrics (cold/warm launch, TTR, TTI, navigation cold/warm TTR, update download, and the TTI frameRate params for triaging slow startups).
Guides agents through a structured 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to opinionated best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage buckets, Compute Engine MIGs, GKE, Cloud Run) to use as load balancer backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancer configurations. - Actuating deployments via Infrastructure Manager or bash scripts, including performing IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
Trigger when: (1) User mentions "manim" or "Manim Community" or "ManimCE", (2) Code contains `from manim import *`, (3) User runs `manim` CLI commands, (4) Working with Scene, MathTex, Create(), or ManimCE-specific classes. Best practices for Manim Community Edition - the community-maintained Python animation engine. Covers Scene structure, animations, LaTeX/MathTex, 3D with ThreeDScene, camera control, styling, and CLI usage. NOT for ManimGL/3b1b version (which uses `manimlib` imports and `manimgl` CLI).