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Found 6,194 Skills
Company discovery and deep research skill. Researches a company's product and ICP, discovers target companies to sell to using Browserbase Search API, deeply researches each using a Plan→Research→Synthesize pattern, and scores ICP fit — compiled into a scored research report and CSV. Supports depth modes (quick/deep/deeper) for balancing scale vs intelligence. Use when the user wants to: (1) find companies to sell to, (2) research potential customers, (3) discover companies matching an ICP, (4) build a target company list, (5) do market research on prospects. Triggers: "find companies to sell to", "company research", "find prospects", "ICP research", "target companies", "who should we sell to", "market research", "lead research", "prospect list".
Use the Browserbase CLI (`browse`) for Browserbase Functions and platform API workflows. Use when the user asks to run `browse`, deploy or invoke functions, manage sessions, projects, contexts, or extensions, fetch a page through the Browserbase Fetch API, search the web through the Browserbase Search API, or scaffold starter templates. Prefer the Browser skill for interactive browsing; use the top-level `browse` driver commands (`browse open`, `browse get`, etc.) only when the user explicitly wants the CLI path.
Understands the Metabase Representation Format — a YAML-based serialization format for Metabase content (collections, cards, dashboards, documents, segments, measures, snippets, transforms). Use when the user needs to create, edit, understand, or validate Metabase representation YAML files, or when working with Metabase serialization/deserialization (serdes). Covers entity schemas, MBQL and native queries, visualization settings, parameters, and folder structure.
Analyze and transform messy, prototype, overgrown, slop-prone, or hard-to-maintain software repositories into maintainable product-shaped codebases while preserving existing product behavior. Use when the user asks to antislop a codebase, clean up a messy repo, run a maintainability migration, write a refactor plan, modernize structure, improve TypeScript/type boundaries, harden tests, reduce large files, clean architecture, coordinate subagent-driven refactors, or produce a final migration audit/report/microsite. Do not use for broader production-readiness specialties such as security audits, observability/logging programs, compliance hardening, SRE/runbook work, or reliability engineering unless the user explicitly scopes those as part of the maintainability refactor.
Wire Firebase Auth (email/password, Google, Apple) and Cloud Firestore into an Ionic Capacitor app. Trigger when adding Firebase Auth, Firestore, social sign-in via Firebase, or backend persistence using Google's Firebase platform.
Use when the user asks for a broad codebase review, substantial PR/branch review, architecture audit, tech-debt scan, cleanup assessment, structural sanity check, or design-alignment review. Default workflow: use sub-agents when available unless specifically forbidden; do not require the user to mention sub-agents, council mode, delegation, or parallel review. Focus on cruft, duplication, weak boundaries, missed reuse, lifecycle/concurrency risks, test/roadmap drift, and code aesthetics. Do not use for narrow bug fixes, ordinary small-diff reviews, frontend visual QA, repo-onboarding docs, or OpenAI Agents SDK production-readiness review. Output evidence-backed findings first, then pressure points, design alignment, open questions, and follow-through.
Build with Firestore NoSQL database - real-time sync, offline support, and scalable document storage. Use when: creating collections, querying documents, setting up security rules, handling real-time listeners, or troubleshooting permission-denied, quota exceeded, invalid query, or offline persistence errors. Prevents 10 documented errors.
Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
Use this skill for reinforcement learning tasks including training RL agents (PPO, SAC, DQN, TD3, DDPG, A2C, etc.), creating custom Gym environments, implementing callbacks for monitoring and control, using vectorized environments for parallel training, and integrating with deep RL workflows. This skill should be used when users request RL algorithm implementation, agent training, environment design, or RL experimentation.
Access RCSB PDB for 3D protein/nucleic acid structures. Search by text/sequence/structure, download coordinates (PDB/mmCIF), retrieve metadata, for structural biology and drug discovery.
Debug database performance issues through query analysis, index optimization, and execution plan review. Identify and fix slow queries.
PocketBase development best practices covering collection design, API rules, authentication, SDK usage, query optimization, realtime subscriptions, file handling, and deployment. Use when building PocketBase backends, designing schemas, implementing access control, setting up auth flows, or optimizing performance.