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Found 1,623 Skills
Implement consumer-driven contract testing with Pact-JS (v16). Covers consumer test writing, broker-driven provider verification, Pact Broker setup, can-i-deploy as a deployment gate, webhook-triggered verification, pending pacts, and schema-first vs consumer-first approaches (OpenAPI/Ajv, Schemathesis). Use when: "contract test," "Pact," "consumer-driven," "API contract," "provider verification," "can-i-deploy." Not for: stubbing or mocking a dependency to isolate a test — use service-virtualization; general REST/GraphQL endpoint assertions against your own API — use api-testing. Related: api-testing, service-virtualization, ci-cd-integration, test-environments.
Audit a whole regression suite and prune/restructure it with evidence: per-test coverage fingerprinting, AST near-duplicate clustering, CI-history mining for never-failing and flaky tests, prune decision rules (redundant/obsolete/low-value/keep), smoke/core/extended tiering by risk and defect-detection history, and a defensible "what we deleted and why" record. Deletion is destructive — quarantine and human sign-off are mandatory. Use when: "audit the test suite," "prune redundant tests," "find duplicate tests," "which tests can we delete," "restructure into smoke/core/extended," "is this test pulling its weight," "shrink the regression suite." Not for: Judging whether an individual test is WELL-WRITTEN (smells, assertions) — that is ai-qa-review. Healing one flaky test at runtime — that is test-reliability. Bulk selector regeneration after a UI refactor — that is selector-drift-recovery. Related: ai-qa-review, coverage-analysis, test-reliability, risk-based-testing, qa-project-context.
Use when building, modifying, or reviewing a Stripe App — or when the user describes something that implies one (e.g. "add a panel to the customer page", "customize my Stripe Dashboard", "react to Stripe events from my app", "connect my service to Stripe without sharing API keys"). Covers the full app development workflow (scaffold, preview, upload, versioning), UI extension architecture (sandboxed iframe, Stripe UI toolkit, viewports), extension types (UI extensions, backend-only, extension interfaces, embedded apps), authentication (platform keys, OAuth, restricted API keys), stripe-app.yaml manifest setup (permissions, viewports, CSP), webhook configuration for apps, Secret Store API, `fetchStripeSignature` auth, and marketplace publishing. Use when the user mentions Stripe Apps, UI extensions, @stripe/ui-extension-sdk, stripe-app.yaml, Dashboard extensions, or customizing the Stripe Dashboard.
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
Guided journey from an app idea to a deliberate architecture: boundaries, domain model, data decisions, and resilience, making only the expensive-to-reverse decisions and deferring the rest. Orchestrates eight skills phase by phase - clean-architecture, domain-driven-design, system-design, ddia-systems, software-design-philosophy, release-it, pragmatic-programmer, 37signals-way - asking the user questions at every decision point and recording results in the project docs/ folder (ARCHITECTURE.md, RELIABILITY.md, DESIGN-CODE-ARCHITECTURE-PLAN.md) so the journey resumes across sessions. Use when the user wants to design a new app's architecture, choose boundaries and a domain model before building, decide monolith versus microservices, or says 'how should I structure this app'. If a codebase already exists, use remove-technical-debt (aged) or improve-code-quality (fresh prototype); if the idea is not validated, run create-business or create-app first. For one framework in isolation, invoke that skill directly.
Use this when setting up a new Redux Toolkit app or modernizing an existing React + Redux codebase. Covers configureStore, Provider wiring, typed hooks, hooks-first React-Redux usage, feature folders, and the correct store lifetime for SPA and SSR-heavy React environments.
Generate or optimize academic paper abstracts using the 5-sentence Farquhar formula. Supports generate-from-scratch and restructure-existing paths. Produces labeled output for formula verification plus a clean version for clipboard use. 摘要生成与优化，支持从原始材料生成或改写现有摘要。
Generate submission-ready cover letters from paper content and target journal requirements. Includes contribution statement, data availability, conflict of interest, and contact block. 生成投稿信，包含贡献声明、数据可用性、利益冲突声明和联系方式。
Manage Todoist tasks, projects, sections, labels, and filters via REST API v2. Supports task CRUD, due dates, priorities, recurring tasks, project organization, and advanced filtering. Based on doggy8088/agent-skills/todoist-api, using curl + jq.
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Interactively create, install, activate, and verify custom claude-mem modes, including domain-specific observation types, concept tags, optional Telegram alerts, bot setup, worker restart, and startup-context verification. Use this whenever someone asks to customize what claude-mem remembers, create or change a mode, track domain-specific notes, add observation types or tags, or send Telegram notifications for particular memories—even if they do not use the word "mode."
Facilitates the fifth step of a proven ideal-customer (ICP) method: mapping inciting events — the specific trigger moments that move a perfect-fit customer from could-buy-someday to buying-today. Takes a keystones file (K1, K2, … with market segments) and, when available, customer-interview findings; walks the keystones one at a time, harvesting real trigger stories from interview evidence (marked observed) and working backward through brainstorm lenses — crises, seasonal cycles, strategic windows, personal life-changes — for the rest (marked hypothesized), recording each event with the keystone it couples to and how to find prospects in that condition, in INCITING-EVENTS.md (E1, E2, …). Load when the user has keystones and asks what makes customers buy now, what triggers a purchase, or 'run the inciting-events step.' Do NOT load to derive keystones or deal-breakers (previous steps), to write the final ideal-customer definition (next step), or to write the ads themselves.