Total 50,633 skills, AI & Machine Learning has 8486 skills
Showing 12 of 8486 skills
Run structured multi-agent debates using argue CLI for cross-examined, high-confidence answers. Use when facing strategic decisions, ambiguous trade-offs, architecture debates, or questions where multiple perspectives improve the answer. Triggers on: argue, debate, cross-examine, second opinion, multi-agent, 'Should we X or Y?' with real stakes, consensus-building, risk analysis, or confirmation-bias mitigation.
Use when you need to read Monologue notes through the public API, search and list a user's notes, fetch a specific note, paginate through all notes, or pull transcripts and summaries with a Monologue Notes API token.
Manage Jetty workflows and assets. Use when the user wants to create, edit, run, deploy, debug, or monitor AI/ML workflows on Jetty. Also use when they mention collections, tasks, trajectories, datasets, models, labels, step templates, or workflow runs. Triggers include 'run workflow', 'create task', 'list collections', 'check trajectory', 'label trajectory', 'add label', 'deploy workflow', 'show results', 'download output', 'debug run', 'workflow failed', or any Jetty/mise/dock operations. Even if the user doesn't say 'Jetty' explicitly, use this skill whenever they're working with Jetty API endpoints, workflow JSON, or init_params.
Monitors AI Gateway traffic, costs, latency, errors, and token usage by querying request traces via the spans query API.
Design predictive maintenance strategies using sensor data, ML models for remaining useful life (RUL), and the P-F curve framework. Use this skill when the user needs to reduce unplanned downtime, transition from reactive to predictive maintenance, evaluate sensor/IoT investments, or estimate equipment failure probability — even if they say 'machines keep breaking down', 'when will this equipment fail', 'should we invest in IoT sensors', or 'reduce unplanned downtime'.
Apply mechanism design (reverse game theory) to engineer incentive-compatible rules for allocation problems. Use this skill when the user needs to design auctions, voting systems, or matching markets, or when evaluating whether a proposed mechanism satisfies incentive compatibility and individual rationality constraints.
Design hybrid recommendation systems combining multiple strategies for improved accuracy. Use this skill when the user needs to overcome single-method limitations, combine collaborative and content-based filtering, or build a production recommendation pipeline — even if they say 'combine recommendation approaches', 'best recommendation architecture', or 'cold start plus personalization'.
Apply Complex Adaptive Systems theory to analyze phenomena exhibiting emergence, self-organization, co-evolution, and edge-of-chaos dynamics. Use this skill when the user needs to understand why a system behaves unpredictably despite known components, model agent-based interactions that produce emergent outcomes, analyze fitness landscapes, or when they ask 'why does this system behave in ways no one designed', 'how do local interactions create global patterns', or 'why do small changes sometimes cause massive system shifts'.
Apply Socratic questioning — systematic inquiry via clarification, assumption-probing, evidence-testing, perspective-shifting, implication-tracing, and meta-questions — to coach learning or surface hidden assumptions in a person's reasoning. Use this skill when the user is explicitly facilitating learning, coaching a person through their own thinking, or needs a structured questioning sequence to probe a held belief, even if they say 'play devil's advocate on this claim' or 'how should I coach my team through this problem via questions'. Do NOT use for open-ended brainstorming, information gathering, or requirements-discovery question lists where no belief is being probed.
GPU Code to Ascend NPU Adaptation Review Expert. When users need to migrate GPU-based code (especially deep learning and model inference-related code) to Huawei Ascend NPU, this skill must be used for comprehensive review. This skill can identify bottlenecks in GPU-to-NPU migration, write adaptation scripts, generate verification plans, and output a complete Markdown review report. Trigger scenarios include: users mentioning keywords such as "NPU adaptation", "Ascend migration", "GPU to NPU", "Ascend", "CANN", "model migration", "operator adaptation", or users requesting to review GPU code repositories and migrate to the NPU platform.
Map migration-relevant Megatron changes onto the official MindSpeed repository by resolving branch alignment, locating affected subsystems, and identifying concrete adaptation points. Use when Codex has structured Megatron change events and needs to decide whether MindSpeed already covers them, which MindSpeed files are likely affected, and whether patch generation is safe.
Optimize the performance of Triton operators optimized for Ascend NPU. This guide is for users who need to optimize the performance of Triton operators on Ascend NPU, resolve UB overflow, improve Cube unit utilization, and design Tiling strategies.