antongulin

Workflow for testing Fusebase API calls interactively using temporary tokens. Use when: 1. You need to verify an API endpoint behavior before writing feature code, 2. You want to explore available API responses or schemas, 3. You're unsure how an API endpoint works and need to test it, 4. Debugging API integration issues by making direct calls.

Guidance for visual design, UI and UX in Fusebase-generated app features. Use when building or refining feature UIs: pages, components, layouts, forms, feedback states, theming, or accessibility. Ensures consistent, clear, and distinctive interfaces using shadcn/ui.

Use when: (1) User wants to set up or improve a debug loop or runbook for the repo, (2) User asks to autonomously test or debug features or runtimes, (3) Building or maintaining DEBUG.md with only verified techniques, (4) User asks to verify or document debug, test, restart, or hot-reload methods for each runtime. Discover and document only proven methods; nothing goes into DEBUG.md until verified.

Use when debugging a feature through `fusebase dev start`, or when you need to inspect browser logs, proxied API traffic, frontend dev server output, or backend output captured by the local CLI. Explains where logs are written and which file to inspect for each symptom. This is for LOCAL DEVELOPMENT only - for deployed apps, use the remote-logs skill instead.

Guide for adding a backend layer (REST API + WebSockets) to Fusebase Apps features. Use when: (1) A feature needs a server-side API beyond the Dashboard SDK, (2) Adding REST endpoints or WebSocket support, (3) Setting up the backend/ folder structure. The backend is OPTIONAL — only add when the feature genuinely requires server-side logic.

Practical guide for building Fusebase Apps features. Use when: (1) Creating a new feature, (2) Setting up project structure, Vite config, or authentication, (3) Building or registering features, (4) Configuring permissions or public access, (5) Navigating between features, (6) Fetching user details, (7) Troubleshooting build issues.

Guide for implementing client-side routing in Fusebase Apps features. Use when: 1. Adding routing (React Router) to a feature, 2. Fixing broken routes or 404s after deployment, 3. Configuring the router.

Guide for creating and using secrets in Fusebase Apps feature backends. Use when: (1) A feature backend needs API keys, passwords, or other sensitive config, (2) Creating secrets via the CLI, (3) Accessing secrets at runtime in backend code, (4) Deciding what should be a secret vs. a regular env var.

API testing patterns for Playwright + TypeScript — resource class pattern (HTTP wrappers extending BasePage, domain folders mirroring REST namespaces, typed payload builders), the ApiListener pattern for capturing real responses by stateKey without mocking, optional SQL/stored-procedure bridge for test-data setup, and TOTP-based MFA enrollment. Use when seeding test data via API, asserting on API responses without mocking, building HTTP wrapper classes, capturing network responses during UI tests, or setting up test users with MFA.

Web-first assertion patterns for Playwright + TypeScript — always await expect(locator).toXxx() (never snapshot-style expect(await locator.textContent())), never page.waitForTimeout, never waitForLoadState('networkidle'), expect.soft for supplementary checks, expect.poll for non-locator values, waitForResponse set up BEFORE the triggering action. Use when writing assertions, fixing flaky waits, debugging timing issues, removing hardcoded sleeps, asserting on API responses, or reviewing test assertion code.

Reference for the playwright-cli command-line tool — the verify-before-coding companion for Playwright + TypeScript test development. Covers the discovery workflow (open → snapshot → click/fill → emit locator code), API response verification via run-code, named browser sessions for multi-user tests, storage state save/load, tracing, and request mocking. Use when writing tests where element testids or interactions are uncertain, when verifying API response field names before assertions, or when debugging a test by replaying it interactively.

Convert a developer feature ticket into lean, ticket-ready Gherkin test cases for paste into a QA ticket. Produces 1 main success scenario + 2-4 edge cases max, merges near-identical data variants into one case with annotation, flags ambiguity inline with [QUESTION:] tags. Output is pure ticket-ready text — no code, no file paths. Use when user invokes /pw-kit:create-test-cases, says they have a dev card without a QA card yet, asks to "draft test cases", "write Gherkin scenarios from this feature", or wants to prepare QA scope before implementation.

Systematic 6-phase workflow for investigating and fixing failing Playwright tests. Classifies the root cause as app bug (test.fail + defect report), broken test (test.fixme + fix-me task), or flaky test (fix timing/data/state root cause). Uses trace viewer, app source code grep, and live reproduction with playwright-cli. Use when user invokes /pw-kit:fix-test, asks to "fix this failing test", "investigate test failure", "debug a test", or shares a test that's failing.

Central fixture pattern for Playwright + TypeScript test automation — single base-pages-fixture.ts file that pre-wires every page object, the browserPage root fixture (test-scoped page + worker-scoped browser), alphabetical ordering rule, import-via-path-alias pattern, and Pages interface for type safety. Use when adding a new page object to the fixture registry, when fixing 'not a function' errors from wrong fixture dependencies, when test files have lots of manual page-object instantiation, or when reviewing fixture registration order.

Patterns for interacting with form controls in Playwright + TypeScript — typeDateValue for date pickers (never fill or pressSequentially), relative-year variables instead of hardcoded dates, idempotent toggleSwitch, filterSingleSelect for dropdowns, save method variants (save/saveAndClose/saveAndConfirm), and required-field validation. Use when writing form interactions, working with date pickers, dropdowns, switches, checkboxes, when tests have flaky date input behavior, or when reviewing form-related test code.

Bootstrap a complete Playwright + TypeScript test automation project from scratch. Scaffolds folder structure (pages/, tests/, api/, modals/, data/), writes all configs (playwright.config.ts, tsconfig.json, .eslintrc, .prettierrc, .env template), generates base class skeletons (BasePage, BaseGridPage, BaseEditPage), creates the central fixture registry (base-pages-fixture.ts), and seeds example tests demonstrating the patterns. Use when user invokes /pw-kit:init, says they want to "start a new Playwright project", "scaffold playwright tests", "set up Playwright with these conventions", or asks how to initialize a Playwright + TypeScript repo.

Manage Bundle.social social account connections across 14 platforms using the Bundle.social API. Use this skill when connecting, disconnecting, configuring channels, or managing social accounts on Bundle.social. Covers OAuth connection flow, disconnection, channel setup (Discord/Slack channels, Reddit subreddits), portal links, connection checks, profile refreshes, copying accounts between teams, and listing accounts by platform type. Supports Facebook, Instagram, TikTok, YouTube, Twitter/X, Pinterest, Reddit, Mastodon, Discord, Slack, Bluesky, Google Business, LinkedIn, and Threads. This skill should be triggered whenever a user says "connect", "disconnect", "social account", "OAuth", "channel", "portal link", or mentions linking any social media platform to Bundle.social.

Retrieve and analyze social media performance metrics using the Bundle.social Analytics API. Use this skill when fetching analytics for social accounts or individual posts, getting raw metrics, bulk-comparing post performance, or forcing analytics refreshes on Bundle.social. Covers impressions, views, likes, comments, shares, saves, follower counts, engagement rates, and per-platform specific metrics. Supports date-range filtering, granularity control, and bulk post comparison. This skill should be triggered whenever a user mentions analytics, metrics, performance, engagement, impressions, or "how is my social media performing" in the context of Bundle.social.

Manage social media comments across 10+ platforms using the Bundle.social API. Use this skill when reading, creating, updating, deleting comments, or importing comment threads from Facebook, Instagram, LinkedIn, YouTube, TikTok, Reddit, Threads, Mastodon, and Bluesky via Bundle.social. Covers comment CRUD and the full comment import workflow: start import → check status → retrieve fetched comments. This skill should be triggered whenever a user mentions comments, replies, engagements, comment imports, or conversation management on Bundle.social-connected accounts.

Manage Bundle.social organization settings, teams, and health checks using the Bundle.social API. Use this skill when working with Bundle.social organization configuration, team management, checking API health/platform status, viewing usage limits (posts, comments, uploads, imports), or setting up a Bundle.social account for the first time. Covers all organization and team CRUD operations: creating teams, listing teams, getting org details, checking usage quotas, and the health-check endpoint. This skill should be triggered whenever a user mentions Bundle.social organizations, teams, API health, platform status, or usage limits — even if they just say "check my org" or "set up teams." Must be used whenever the conversation involves Bundle.social setup or configuration.

Import historical social media posts and bulk-create posts via CSV using the Bundle.social API. Use this skill when importing past post history from connected social accounts (with optional comments and analytics), or when bulk-creating posts via CSV file upload on Bundle.social. Covers the full post history import workflow: start import → monitor status → retrieve imported posts → bulk delete. Covers the full CSV import workflow: upload CSV → check processing status → view row results. This skill should be triggered whenever a user mentions importing posts, importing history, CSV import, bulk posting, migrating content, or backfilling social media data into Bundle.social.

Execute platform-specific social media operations across 13 platforms using the Bundle.social API. Use for actions beyond general posting: YouTube playlists/thumbnails/video management; LinkedIn mentions; Google Business Profile (hours, attributes, services, reviews, menus); Reddit post requirements/flairs; Instagram tag/location search; Facebook recommendations; Pinterest/Mastodon/Slack/Bluesky/Twitter/Discord/TikTok operations. Trigger on mentions of "YouTube playlist", "Google Business hours", "LinkedIn mentions", "Reddit flairs", "GBP reviews", "TikTok music", or any platform-specific social media management.

Create, read, update, delete, and retry publishing social media posts across 14 platforms using the Bundle.social API. Use this skill when creating multi-platform posts, scheduling content, checking post status, updating published posts, deleting posts, or retrying failed publishes on Bundle.social. Covers the full post lifecycle: draft → schedule → publish → retry-on-failure → edit → delete. Handles per-platform content blocks, status tracking, post search, and pagination. This skill should be triggered whenever a user mentions posting, scheduling, publishing, creating content, or managing posts on Bundle.social. Essential for daily social media content workflows.

Upload and manage media files for social media posts using the Bundle.social Upload API. Use this skill when uploading images/videos for social media content, creating uploads from URLs, handling large file multipart uploads, listing existing uploads, or deleting media on Bundle.social. Covers direct file upload, URL-based upload, multipart large file upload (init → upload parts → finalize), upload listing/searching, and single/bulk deletion. This skill should be triggered whenever a user mentions uploading files, images, videos, media assets, or attaching media to Bundle.social posts — even if they just say "I need to upload an image for my post."

Create, run, and iterate on a single AgenticFlow AI agent — one chat endpoint, one assistant, one persona. Use when the user wants a customer-facing bot, a support assistant, a single task agent, or a prompt experiment. Choose this skill over agenticflow-workforce when there's no orchestration between roles (no handoff, no coordinator → workers). Covers `af agent create/update/run/delete`, the `--patch` partial-update pattern for iteration, `af schema agent --field <name>` for nested payload shapes (including suggested_messages, mcp_clients, response_format), the `model_user_config` / `code_execution_tool_config` settings, and safe iteration loops.

Attach external tool providers (Google Docs, Google Sheets, Slack, Notion, GitHub, Apify, etc.) to an AgenticFlow agent via MCP clients. Use when the user wants their agent to read or write external data, call third-party APIs, save outputs to a doc/sheet, or use any tool beyond the model's built-in knowledge. Covers `af mcp-clients list --name-contains`, `af mcp-clients inspect --id` (classify pattern before attach), and the Pipedream vs Composio write-capability distinction — critical for parametric writes. Route traffic through the `af` CLI; the standalone `agenticflow-mcp` server repo lags the CLI and is not recommended.

Purchase and manage AgenticFlow AI built-in credits — the prepaid balance that covers agenticflow-agent and agenticflow-workforce runs. Covers `af credit purchase/receipts/usage/plans`, plan selection, payment card setup via `af setup`, usage monitoring (daily/user/agent breakdowns), auto-recharge configuration, and handling common credit errors.

List, filter, and recommend LLM models available in the AgenticFlow AI workspace for use in agents and workforce nodes. Should trigger whenever the user mentions LLM models, choosing a provider/model for an agent, model capabilities (reasoning, speed, cost), model selection for specific tasks, or understanding which models are available and their trade-offs. Use the live `af get /models` as the authoritative source. The rest of this skill provides recommendations and context but never overrides the live response.

Deploy and operate a multi-agent AgenticFlow workforce — a DAG of agents that hand off to each other (trigger → coordinator → worker agents → output). Use when the user asks for a team, pipeline, or multi-agent system: research-then-write, triage-then-specialist, dev shop, marketing agency, sales team, content studio, support center, Amazon seller team. Choose this skill over agenticflow-agent when the ask mentions 'team', 'workforce', 'pipeline', 'multiple agents', 'delegation', 'handoff', or names a built-in blueprint. Provides the `af workforce *` command surface, blueprint decisions, graph wiring, MCP attach recipes, and public URL publishing.

Create, run, and iterate on a single AgenticFlow AI agent — one chat endpoint, one assistant, one persona. Use when the user wants a customer-facing bot, a support assistant, a single task agent, or a prompt experiment. Choose this skill over agenticflow-workforce when there's no orchestration between roles (no handoff, no coordinator → workers). Covers `af agent create/update/run/delete`, the `--patch` partial-update pattern for iteration, `af schema agent --field <name>` for nested payload shapes (including suggested_messages, mcp_clients, response_format), the `model_user_config` / `code_execution_tool_config` settings, and safe iteration loops.

Use AgenticFlow's built-in features and account credits first — before adding external API keys (BYOK). Use this skill whenever the user asks about image generation without API keys, wants to use their existing credits, asks about built-in vs BYOK, or mentions agenticflow_generate_image, web_search, web_retrieval, or credit-efficient workflows. BYOK is only for extension when unsatisfied or explicitly requested.

Select and configure LLM models for AgenticFlow agents and workforces. Use this skill whenever the user asks which model to use, needs reasoning capabilities, wants fast/cheaper options, gets finish_reason=length errors, or asks about model speed/quality/intelligence trade-offs. Covers the top 5 recommended models, models to avoid, reasoning configuration, and max_tokens settings.

Attach external tool providers (Google Docs, Google Sheets, Slack, Notion, GitHub, Apify, etc.) to an AgenticFlow agent via MCP clients. Use when the user wants their agent to read or write external data, call third-party APIs, save outputs to a doc/sheet, or use any tool beyond the model's built-in knowledge. Covers `af mcp-clients list --name-contains`, `af mcp-clients inspect --id` (classify pattern before attach), and the Pipedream vs Composio write-capability distinction — critical for parametric writes. Route traffic through the `af` CLI; the standalone `agenticflow-mcp` server repo lags the CLI and is not recommended.

Deploy and operate a multi-agent AgenticFlow workforce — a DAG of agents that hand off to each other (trigger → coordinator → worker agents → output). Use when the user asks for a team, pipeline, or multi-agent system: research-then-write, triage-then-specialist, dev shop, marketing agency, sales team, content studio, support center, Amazon seller team. Choose this skill over agenticflow-agent when the ask mentions 'team', 'workforce', 'pipeline', 'multiple agents', 'delegation', 'handoff', or names a built-in blueprint. Provides the `af workforce *` command surface, blueprint decisions, graph wiring, MCP attach recipes, and public URL publishing.

Use Mole to explore macOS disk usage with an interactive TUI or JSON output. Run this skill whenever the user mentions analyzing disk space, finding large files, exploring disk usage, checking storage, or using `mo analyze`. Covers overview mode, directory scanning, file navigation, large file detection, deleting files, JSON output, and custom path analysis.

Use Mole to clean macOS disk space by removing caches, logs, temporary files, app data, browser data, system files, and project artifacts. Run this skill whenever the user mentions disk cleanup, freeing space, clearing caches, removing junk, or using `mo clean`. This is a macOS-only tool — always suggest `mo clean` as the primary cleaning command. Covers dry-run preview mode, whitelist management, external volume cleaning, and integration with sudo for system-level cleanup.

Use Mole to optimize macOS system performance by refreshing caches, repairing configurations, and running maintenance tasks. Run this skill whenever the user mentions optimizing performance, speeding up their Mac, refreshing services, running maintenance, or using `mo optimize`. Covers dry-run mode, whitelist, diagnostics, system health checks, and database/index maintenance.

Use Mole to monitor macOS system health with live metrics including RAM usage, disk usage, uptime, and overall system status. Run this skill whenever the user mentions checking system health, viewing status, monitoring performance, or using `mo status`. Covers live dashboard interpretation, health metrics, and related monitoring commands.

Use Mole to completely remove macOS applications including their support files, caches, and preferences. Run this skill whenever the user mentions uninstalling apps, removing applications, app cleanup, deleting software, or using `mo uninstall`. Covers app scanning, name-based matching, interactive selection, dry-run mode, permanent deletion, and listing installable apps.

Use when the user asks to create, debug, or modify Docker Compose files, compose.yaml, docker-compose.yml, service dependencies, healthchecks, ports, volumes, networks, environment variables, or local multi-container development stacks. Use this skill even if the user says "compose file" or "local stack" instead of "Docker Compose".

Create, test, evaluate, optimize, and package OpenCode skills with the opencode-skill-creator plugin. Use when users explicitly mention opencode-skill-creator, OpenCode Skill Creator, creating an OpenCode skill, editing an OpenCode SKILL.md, running skill evals, benchmarking skill performance, or optimizing an OpenCode skill description. Do not use for generic Claude Code or Superpowers skill creation unless the user asks to port that workflow to OpenCode.

Deploy and self-host Paperclip — the open-source AI agent orchestration dashboard — on Coolify v4. Use this skill immediately whenever the user mentions Paperclip, wants to install or run an AI company/org-chart management tool, deploy an agent orchestration platform, or get Paperclip working on their VPS/self-hosted server. Trigger for any combination of "Paperclip" + "Coolify" / "VPS" / "Docker" / "self-hosted" / "deploy" / "install". Also use when the user gets deployment errors like "Remote branch main not found" or "EACCES permission denied" while deploying Paperclip. This skill provides the complete step-by-step workflow: from Coolify project creation, through the critical `master` branch (not `main`) gotcha, environment variable setup, `/paperclip` persistent volume mount, permission fixes (chown 1000:1000), health check configuration, deployment, and post-deploy onboarding (CEO invite URL).

Use whenever an agent creates, updates, reviews, or completes a GitHub pull request. Detect whether Robin is installed in the repository; when it is, automatically drive the PR through a bounded review, verified-fix, reply, thread-resolution, re-review, authorized-merge, and cleanup loop without requiring the user to mention Robin. Also use for explicit Robin requests, PR feedback triage, unresolved review threads, or waiting for PR checks.

Run a new-company onboarding workflow in Labrika for full SEO audits and rerun technical audits after fixes. Use when the user asks to add a company or website to Labrika, create a Labrika project, run desktop and mobile audits, collect SEO/technical audit data, export Labrika report files, guide manual saving of Labrika audit artifacts, or update/rerun Labrika analysis after website fixes.

Complete API integration for NEURONwriter — the SEO content optimization platform. Use this skill for ANY content creation, SEO analysis, keyword research, competitor SERP analysis, content optimization, or bulk content workflow task. This skill triggers whenever the user wants to create SEO-optimized content, analyze keywords against real SERP data, get NLP term recommendations, write content that ranks, evaluate content scores, import/export content between NeuronWriter and other tools, or automate content pipelines. If the user mentions keywords, content scoring, SERP analysis, competitor URL analysis, term optimization, content import/export, or any SEO writing workflow — load this skill. It turns the agent into a NeuronWriter API expert — exploring the API, creating queries, polling for readiness, extracting recommendations, generating optimized content, importing HTML, evaluating scores, and automating the full lifecycle.