Total 31,058 skills, AI & Machine Learning has 5021 skills
Showing 12 of 5021 skills
ORCA v1.1 — Hardened dual-mode emerging movers scanner. Every lesson from 5+ days of live trading across 22 agents baked into the code. v1.1 adds the DSL state template directly in scanner output — eliminating the dsl-profile.json override bugs that broke Fox, Grizzly, Jackal, and every Wolf-based agent. XYZ equities banned at scan level. Leverage 7-10x enforced. Stagnation TP mandatory. 10% daily loss limit. 2-hour per-asset cooldown. Conviction-scaled Phase 1 timing per-signal. The agent cannot override any of these — they are in the scanner, not instructions.
The project's all-seeing guide. Sentinel MUST activate before Claude takes any action that modifies, creates, or deletes anything in the project. It understands the codebase, architecture, brand, design system, business model, deployment pipeline, testing strategy, and every convention. Trigger on: action requests (build, fix, add, change, update, refactor, implement, create, remove, delete, migrate, deploy, integrate, improve, configure, install, bump, upgrade, debug, troubleshoot, move, rename); casual requests (can you, I need to, let's, go ahead and, help me, we need to); status reports (X is broken/failing, there's a bug); project questions (how does X work here, where would I add, walk me through); planning (scope this, break this down, write a spec). Do NOT trigger on general knowledge, blog posts, interview prep, or tech comparisons for other projects. Key test: does this need THIS project's context? If yes, trigger. Sentinel guides Claude, it does not execute. No task is too small.
Aids in writing Mojo code that interoperates with Python using current syntax and conventions. Use this skill in addition to mojo-syntax when writing Mojo code that interacts with Python, calls Python libraries from Mojo, or exposes Mojo types/functions to Python. Also use when the user wants to build Python extension modules in Mojo, wrap Mojo structs for Python consumption, or convert between Python and Mojo types.
The basics of how to program GPUs using Mojo. Use this skill in addition to mojo-syntax when writing Mojo code that targets GPUs or other accelerators. Use targeting code to NVIDIA, AMD, Apple silicon GPUs, or others. Use this skill to overcome misconceptions about how Mojo GPU code is written.
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
Set up or log in to Karma. Use when user says "set up agent", "configure API key", "connect to Karma", "login to Karma", "log in", or before first use of any Karma skill.
Create new Claude Code skills for the Karma ecosystem. Use when user says "create a skill", "build a new skill", "scaffold a skill", or "design a skill". Guides through intent capture, SKILL.md writing, validation, and packaging.
Clarify ambiguous or conflicting requests by researching first, then asking only judgment calls. Use when prompts say "$grill-me"/"grill me", ask hard questions, request relentless interrogation, pressure-test assumptions, clarify scope/requirements, define success criteria, or request system-design/optimization decisions before implementation; stop before implementation.
Use when building any system where email content triggers actions — AI agent inboxes, automated support handlers, email-to-task pipelines, or any workflow processing untrusted inbound email. Always use this skill when the user wants to receive emails and act on them programmatically, even if they don't mention "agent" — the skill contains critical security patterns (sender allowlists, content filtering, sandboxed processing) that prevent untrusted email from controlling your system.
Exposes Claude's reasoning chain as an auditable, decomposable artifact. Quick mode (default) gives assumption inventory + weakest-link in 2 stages. Full mode (--full) adds decision branching, confidence decomposition, and falsification conditions. Triggers on "왜 그렇게 생각해", "reasoning", "근거", "show your work", "어떻게 그 결론이", "trace", "판단 근거", "why do you think that".
Curate a Chinese reading digest from a fixed bundle of RSS and Atom feeds, with a strong preference for AI agent thinking, frontier AI commentary, deep interviews, and non-boring high-signal essays. Use when Codex needs to pull the latest week's posts by default, or a specific day's posts when explicitly requested, summarize them, score each article on a 10-point scale, and output only the posts scoring above 7 in a concise Chinese daily-brief style.
Real-time global intelligence dashboard with AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking