Loading...
Loading...
Found 4,647 Skills
Generate reference documentation entry by entry for the public surface of libraries (components, functions, commands, etc.), with manifest tracking, supporting both single-entry and batch modes. Fundamental differences from guidedoc: guidedoc teaches you how to use things, while libdoc tells you what each part looks like; guidedoc's information sources are solution docs + user knowledge, while libdoc's information source is the source code itself. Trigger scenarios: When users say "write API documentation", "component documentation", "libdoc", "write documentation for each component", or when new public library interfaces are found after feature-acceptance.
Shows a structured progress dashboard for an album with percentage complete per phase, blocking items, and status breakdown. Use for a quick visual overview of album progress.
Workflow 4: Submission rebuttal pipeline. Parses external reviews, enforces coverage and grounding, drafts a safe text-only rebuttal under venue limits, and manages follow-up rounds. Use when user says "rebuttal", "reply to reviewers", "ICML rebuttal", "OpenReview response", or wants to answer external reviews safely.
Kuikly Exposure & Visibility Event Development Assistant (Kuikly DSL). It guides how to use five visibility events including didAppear, didDisappear, willAppear, willDisappear, and appearPercentage to implement functions such as component exposure reporting, visibility percentage monitoring, list item exposure statistics, etc. It is used when users need to implement scenarios like exposure reporting, visibility monitoring, list item exposure statistics, visibility percentage calculation in Kuikly.
Autonomously research a topic via multi-round web search, synthesize findings, and file structured results into the Obsidian wiki. Use this skill when the user says "/wiki-research [topic]", "research X", "find everything about Y", "do a deep dive on Z", "autonomous research on X", or wants comprehensive, web-sourced knowledge on a topic filed directly into their wiki.
LLM-as-a-judge HTTP/HTTPS proxy that secures AI agents by intercepting and evaluating outbound requests against security policies before they reach external APIs.
Grafana Cloud account management — organizations, stacks, RBAC, SSO/SAML/OAuth, service accounts, API keys, team management, billing, and cloud-level provisioning. Use when managing Grafana Cloud access, configuring SSO, setting up service accounts for CI/CD, assigning roles, managing multiple stacks or organizations, or provisioning cloud resources via API.
Planhat platform help — Health Scores, Agentic Automation, Revenue Management, CRM Sync, Enduser Tracking, Projects, NPS, REST API, MCP Server. Use when health scores aren't reflecting churn risk, CRM sync is overwriting fields or not pulling data, metrics take hours to build and formulas keep breaking, automation rules aren't triggering, revenue or license data doesn't match Salesforce, enduser tracking isn't capturing product usage, or the Planhat API returns unexpected errors. Do NOT use for general customer success strategy (use /sales-customer-success) or NPS/CSAT survey methodology (use /sales-customer-feedback).
Open-source Chrome extension replacing 12+ browser extensions with privacy-respecting tools including tab cleaner, cookie editor, dark mode, JS toggle, GDPR dismisser, and more.
Build modern data apps, dashboards, and interactive reports using either React + Vite or Streamlit. Includes optional Gemini Data Analytics chat integration for an AI powered "chat with your data" experience. Relevant when any of the following conditions are true: 1. User explicitly requests to build a data dashboard, data application, or visualization UI, and the UI pulls data from a GCP database (defaulting to BigQuery unless otherwise specified). 2. You need to generate a frontend web application to interact with, query, and visualize data from GCP data sources. 3. User wants to build a "chat with your data" experience or integrate the Gemini Data Analytics chat API into a web interface. Do NOT use when any of the following conditions are true: 1. The request is for building backend-only services. 2. The request is for simple CLI scripts or command-line applications. 3. The web application is not data-centric or does not involve visualizing/querying data from GCP sources.
Expertise in generating clean, correct, and efficient Dataform pipeline code for BigQuery ELT. Use this when creating or modifying Dataform pipelines, actions, or source declarations, when Dataform, SQLX, or BigQuery are mentioned in a transformation, when data needs to be ingested from GCS into BigQuery via Dataform, or when setting up a new Dataform project or configuring workflow_settings.yaml.
Use when the user wants to extract, generate, refine, or harden an OpenAPI or Swagger specification from an existing API application, service, project, repo, routes, controllers, handlers, or codebase. Select this skill for any request whose intent is to derive, extract, generate, reverse-engineer, infer, document, or harden an OpenAPI or Swagger contract from an existing application or source code. This includes generic prompts about producing an API spec/docs/schema/contract for an existing app, project, service, repo, endpoints, routes, or controllers. Prefer this skill over extraction-only skills when the prompt is about an existing application or codebase and the expected outcome is an accurate extracted contract plus post-extraction refinement.