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Found 1,833 Skills
Run an end-to-end workflow that chains `research-refine` and `experiment-plan`. Use when the user wants a one-shot pipeline from vague research direction to focused final proposal plus detailed experiment roadmap, or asks to "串起来", build a pipeline, do it end-to-end, or generate both the method and experiment plan together.
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
Use when setting up CI/CD, Docker, deployment pipelines, monitoring, alerting, infrastructure, or debugging production issues
Structured specification with explicit scope boundaries: user stories, acceptance criteria, out-of-scope definition, risks, and estimation. Positions before feature-design in the feature lifecycle pipeline. Use when: "write spec", "user stories", "define requirements", "scope this", "what should this do", "acceptance criteria", "define scope"
Create a new voice profile from writing samples. 7-phase pipeline: Collect, Extract, Pattern, Rule, Generate, Validate, Iterate. Wabi-sabi (natural imperfections as features) is the core principle. Use when creating a new voice, starting voice calibration, or building a voice profile from scratch. Use for "create voice", "new voice", "build voice", "voice from samples", "calibrate voice". Do NOT use for generating content in an existing voice (use voice-orchestrator), editing content (use anti-ai-editor), or comparing voices (use voice-calibrator compare mode).
Generate emulate seed configs for stateful API emulation. Wraps Vercel's emulate tool for GitHub (repos, PRs, issues, Actions, webhooks), Vercel (projects, deployments, domains), and Google OAuth APIs. Not mocks — full state machines where create-a-PR-and-it-appears-in-the-list. Use when setting up test environments, CI pipelines, integration tests, or offline development.
Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Azure Load Testing with VNets/private endpoints, JMeter/Locust/Playwright, CI/CD pipelines, or Playwright Workspaces, and other Azure App Testing related development tasks. Not for Azure Test Plans (use azure-test-plans), Playwright Workspaces (use azure-playwright-workspaces), Azure DevOps (use azure-devops), Azure App Service (use azure-app-service).
Inspect deal health, map stakeholders, identify risks, and recommend next actions. Use when reviewing a deal, assessing deal health, doing a MEDDPICC assessment, mapping stakeholders, analyzing deal risk, prepping for a deal review, inspecting pipeline deals, or evaluating champion strength. Do NOT use for portfolio-level pipeline management (use /sales-pipeline), revenue forecasting (use /sales-forecast), or reviewing a specific sales call (use /sales-call-review).
Retrieve ALL information from a Jira ticket (description, comments, subtasks, attachments metadata, labels, sprint, status, assignee, reporter, linked issues, custom fields, acceptance criteria) and persist it as a single Markdown file. Use whenever the user says "fetch ticket", "retrieve Jira", "pull ticket info", "get ticket details", "look up ticket", "grab the Jira", "what does ticket X say", "check the ticket", "read the ticket", "show me the ticket", or provides a Jira ticket URL or key like PROJECT-1234. Also triggered by the orchestrating-jira-workflow skill as Phase 1 of the end-to-end pipeline. Trigger even if the user only pastes a ticket key with no other context — that alone means "fetch this ticket." This skill ONLY retrieves — it never modifies the ticket or starts implementation.
Configurable pipeline orchestrator for sequencing stages
When the user wants to audit a Google Ads account for a lead generation business — reviewing CPL, lead volume, lead quality, form conversion rates, offline conversion imports, and pipeline-focused optimization. Triggers on 'lead gen audit', 'Google Ads audit lead generation', 'CPL audit', 'audit my lead gen account', 'B2B Google Ads audit', 'lead quality audit', 'cost per lead audit', 'lead gen account review', or 'review lead generation Google Ads'. For general account audits see google-ads-account-audit. For ecommerce audits see google-ads-audit-ecommerce.
Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL. Invoke BEFORE starting implementation.