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All Skills

Total 50,542 skills, AI & Machine Learning has 8483 skills

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Showing 12 of 8483 skills

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AI & Machine Learningflc1125/skills

experts

Assemble a panel of experts to assess a problem from multiple professional perspectives, surface agreement and disagreement, and deliver a chaired recommendation with clear tradeoffs. Use when the user wants multi-expert judgment, a second opinion, design critique, option comparison, or a recommendation backed by distinct expert viewpoints.

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8
AI & Machine Learningwilliamhallatt/cogworks

cogworks

Start here — turn source material into a validated agent skill. Orchestrates cogworks-encode (synthesis) and cogworks-learn (skill generation).

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8
AI & Machine Learningmounirdhahri/skills

agentsmd-claudemd-generator

Generate AGENTS.md and CLAUDE.md files for a repository. AGENTS.md provides cross-tool agent instructions (supported by Claude Code, Cursor, Windsurf, Zed, Codex, and others). CLAUDE.md adds Claude-specific configuration and references AGENTS.md via @import. Use when a repo needs agent onboarding or when starting a new project.

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8
AI & Machine Learningbmad-code-org/bmad-method

bmad-quick-dev

Implements any user intent, requirement, story, bug fix or change request by producing clean working code artifacts that follow the project's existing architecture, patterns and conventions. Use when the user wants to build, fix, tweak, refactor, add or modify any code, component or feature.

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8
AI & Machine Learningmorphiqlabs/morphiq-labs-...

morphiq-build

This skill should be used when the user asks to "fix the issues", "optimize existing content", "create new content for AI visibility", "run Morphiq Build", "generate schema markup", "create an llms.txt file", "run the content lab", or mentions building content fixes, generating schema, rewriting content for AI citations, or creating policy files. Consumes a Prioritized Roadmap (or user prompt, or existing content) and produces build artifacts through a 6-step content lab pipeline.

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8
12 scripts/Attention
AI & Machine Learningwebmaxru/ai-native-dev

agent-package-manager

Installs, configures, audits, and operates Agent Package Manager (APM) in repositories. Use when initializing apm.yml, installing or updating packages, validating manifests, managing lockfiles, compiling agent context, browsing MCP servers, setting up runtimes, or packaging resolved context for CI and team distribution. Don't use for writing a single skill by hand, generic package managers like npm or pip, or non-APM agent configuration systems.

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8
AI & Machine Learninggracefullight/stock-check...

coordinate

Task-based multi-agent coordination (includes Issue Remediation Loop)

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8
AI & Machine Learningtradermonty/claude-tradin...

edge-strategy-reviewer

Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategy_drafts/*.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores.

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8
3 scripts/Attention
AI & Machine Learningteneoprotocolai/teneo-ski...

vc-attention-teneo

Overview The VC Attention Agent allows users to extract followings of top crypto VCs, including lists from Dragonfly, Paradigm, a16z, and more, to bypass manual mapping and identify where institutiona

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8
AI & Machine Learningqdrant/skills

qdrant-clients-sdk

Qdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.

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8
AI & Machine Learningdontbesilent2025/claude-s...

lacan

Lacanian psychoanalysis dialogue. Conduct analytical dialogues based on Lacanian theoretical framework (big Other, desire, fantasy, signifier chain). Trigger methods: /lacan, "Lacan", "psychoanalysis dialogue" Lacanian psychoanalysis dialogue using Lacanian framework (big Other, desire, fantasy, signifier chain). Trigger: /lacan, "Lacanian analysis", "psychoanalysis dialogue"

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8
AI & Machine Learningawslabs/agent-plugins

dataset-evaluation

Validates dataset formatting and quality for SageMaker model fine-tuning (SFT, DPO, or RLVR). Use when the user says "is my dataset okay", "evaluate my data", "check my training data", "I have my own data", or before starting any fine-tuning job. Detects file format, checks schema compliance against the selected model and technique, and reports whether the data is ready for training or evaluation.

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1 scripts/Checked
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