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Found 1,850 Skills
Decompose input into a structured task backlog for automated agent loops. Use when asked to "create a task plan", "break this into tasks", "decompose this PRD", "turn this into a backlog", or "plan tasks from" any input source (PRD, Figma feedback, GitHub issues, user requirements). Also use when the user provides a PRD, design doc, or requirements and wants executable tasks, even if they don't mention "task plan" explicitly.
Use this skill when the user asks to call an authenticated HTTP API (for example "call the GitHub/OpenAI/Slack API", "hit an endpoint that needs a bearer token") and the `sesame` CLI is already installed on this device. The agent invokes `sesame request`, which forwards the HTTP call through the user's own broker and attaches the auth header server-side. The skill does not install software, does not read credentials from the environment, and runs shell only within the fixed `sesame` subcommand surface (`request`, `status`, `hostnames`, `login`, `refresh`). Skip for unauthenticated public endpoints, localhost services, or when the user has already exported a token in the environment for direct use.
Analyze community opinions from forums and comment sections. Scrapes comments from Bilibili, Reddit, or GitHub Issues, clusters them by semantic similarity, and extracts the core arguments, debates, and viewpoints. Produces a structured report showing what the community actually thinks — not just a summary of comments, but the underlying positions people hold and where the real disagreements are. Use this skill when the user wants to understand public opinion on a topic, find the main points of contention in a discussion, or do competitive/event research from community sources. Triggers include requests to "analyze comments", "what are people saying about X", "summarize the debate", "find the key arguments", "what's the community consensus", or any task involving opinion extraction from forum or comment data.
Use the Helmor CLI to remote-control Helmor from the terminal. Use when the user asks to inspect Helmor data/settings, manage repositories/workspaces/sessions/files, send prompts to agents, list models, use GitHub integration, inspect scripts, migrate from Conductor, run Helmor as an MCP server, generate shell completions, quit a running app, check/install/update the Helmor CLI beta, install/update Helmor skills through the beta app flow, or needs the Helmor command reference.
Guides all better-i18n integration decisions — SDK selection (Next.js, React, Expo, Swift, Flutter, Remix), CDN vs GitHub workflow, AI-powered translation management via MCP tools, CLI health checks (scan, doctor, sync), Content CMS (localized models, entries, custom fields), file format conventions (flat / nested / namespaced), key naming, publish flows, and quality analytics. Use whenever building, modifying, or reviewing any localization feature — including i18n setup, adding languages, managing translation keys, publishing, or integrating AI workflows.
Implement secure webhook handling with signature verification, replay protection, and idempotency. Use when receiving webhooks from third-party services like Stripe, GitHub, Twilio, or building your own webhook system.
Smart Disk Cleaner for Mac, a user-friendly wrapper based on Mole (https://github.com/tw93/Mole)
Track deep work sessions locally (start/stop/status) and generate a GitHub-contribution-graph style minutes-per-day heatmap for sharing (e.g., via Telegram). Use when the user says things like “start deep work”, “stop deep work”, “am I in a session?”, “show my deep work graph”, or asks to review deep work history.
Release your software. Pre-flight validation, changelog generation, version bumps, release commit, tag, draft GitHub Release. Boundary: everything up to the git tag. Triggers: "release", "cut a release", "prepare release", "release check".
Guides developers through testing Tauri applications including unit testing with mock runtime, mocking Tauri APIs, WebDriver end-to-end testing with Selenium and WebdriverIO, and CI integration with GitHub Actions.
Creates and maintains dlt (data load tool) pipelines from APIs, databases, and other sources. Use when the user wants to build or debug pipelines; use verified sources (e.g. Salesforce, GitHub, Stripe) or declarative REST API or custom Python; configure destinations (e.g. DuckDB, BigQuery, Snowflake); implement incremental loading; or edit .dlt config and secrets. Use when the user mentions data ingestion, dlt pipeline, dlt init, rest_api_source, incremental load, or pipeline dashboard.
Build professional visibility through LinkedIn, GitHub, conference speaking, and internal branding. Provides frameworks for personal brand development, content creation, and career growth.