Loading...
Loading...
Found 736 Skills
Search data using vector similarity, full-text keywords, or hybrid methods with Reciprocal Rank Fusion (RRF). Use when setting up embeddings for search, configuring full-text indexing, writing vector_search/text_search/rrf SQL queries, using the /v1/search HTTP API, or configuring vector engines like S3 Vectors.
Comprehensive trading skills system with multi-broker support, strategy execution, and autonomous trading capabilities
Enhanced reasoning patterns via slash commands (/think, /verify, /adversarial, /edge, /compare, /confidence, /budget, /constrain, /json, /flip, /assumptions, /tensions, /analyze, /trade) or natural language ("argue against", "what could break", "show reasoning", "deep review", "meta-prompts", "thinking modes", "second-best approach", "list assumptions", "opposing perspectives").
Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots. Use when the user mentions "continuous discovery", "opportunity solution tree", "weekly interviews", "assumption testing", or "discovery habits". Covers experience mapping, co-creation, and prioritizing opportunities. For interview technique, see mom-test. For team structure, see inspired-product.
Structure software around the Dependency Rule: source code dependencies point inward from frameworks to use cases to entities. Use when the user mentions "architecture layers", "dependency rule", "ports and adapters", "hexagonal architecture", or "use case boundary". Covers component principles, boundaries, and SOLID. For code quality, see clean-code. For domain modeling, see domain-driven-design.
Orchestrates Jira ticket creation from Figma designs using Atomic Design principles. Use this when initializing a project or syncing design specs to Jira for development.
Listen for one or more IMAP inboxes with the IDLE command, fetch unread email metadata plus text previews, and forward each message to OpenClaw webhooks. Use when tasks need near-real-time mailbox monitoring, multi-account inbox ingestion via environment variables, and automatic trigger delivery into OpenClaw automation.
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or the loop cap is reached. Use when: implementing features from a spec or plan, hardening existing code, fixing a batch of issues, or any multi-file task that benefits from a build-verify-fix cycle.
CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.
Checks a GitHub pull request for unresolved review comments, failing status checks, and incomplete PR descriptions. Waits for pending checks to complete, categorizes issues as actionable or informational, and optionally fixes and resolves them. Use when the user wants to check a PR, address review feedback, or prepare a PR for merge.
To be used when the user mentions tasks related to ARCS/arcs-sdk, cross-compilation toolchain (riscv64-unknown-elf-gcc), cskburn, flashing, /dev/ttyACM*, serial port logs, etc.: Responsible for repository pulling, environment setup, compilation, flashing, running and log reading; Not responsible for code writing/understanding, code development is handled by Claude Code itself
Auto-fix CodeRabbit review comments - get CodeRabbit review comments from GitHub and fix them interactively or in batch