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All Skills

Total 55,866 skills, AI & Machine Learning has 9293 skills

Categories

Showing 12 of 9293 skills

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AI & Machine Learningshoootyou/get-shit-done-m...

gsd-set-profile

Switch model profile for GSD agents (quality balanced budget)

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12
AI & Machine Learningshoootyou/get-shit-done-m...

gsd-discuss-phase

Gather phase context through adaptive questioning before planning

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12
AI & Machine Learninggleanwork/glean-cli

glean-cli-agents

List, inspect, and run Glean AI agents. Use when discovering available agents, viewing agent schemas, or invoking agents programmatically.

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12
AI & Machine Learningpproenca/dot-skills

diagram-quality

Use this skill whenever calling agent-uml MCP tools (design_create, diagram_upsert, design_feedback, design_export) to render PlantUML diagrams on the collaborative canvas. Covers three tiers — rendering safety (syntax that prevents HTTP 400 blank canvas), conversation mechanics (when to push a version vs ask a question, what to write in the message parameter), and design effectiveness (decomposition thresholds, cross-diagram traceability, export readiness). Trigger even when the task seems simple — a missing `as alias` makes elements un-annotatable, and a skinparam mismatch makes diagrams unreadable on the warm

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12
AI & Machine Learningflora131/atomic

context-fundamentals

The foundational context engineering skill — start here when exploring the discipline. This skill should be used when the user asks to "understand context", "explain context windows", "design agent architecture", "debug context issues", "optimize context usage", or discusses context components, attention mechanics, progressive disclosure, or context budgeting. Also activates when the user mentions "context engineering" or "context-engineering" for foundational understanding of AI agent context systems.

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12
1 scripts/Checked
AI & Machine Learningasgard-ai-platform/skills

grad-cas

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'.

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12
AI & Machine Learningasgard-ai-platform/skills

algo-rec-mf

Implement matrix factorization to decompose user-item interaction matrices into latent factor representations. Use this skill when the user needs scalable collaborative filtering, latent feature discovery, or dimensionality reduction for recommendation — even if they say 'SVD recommendations', 'latent factors', or 'factorize the rating matrix'.

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12
AI & Machine Learningascend/agent-skills

ascendc-operator-precision-eval

AscendC Operator Precision Evaluation. Generate a comprehensive precision test case set (≥30 cases) for the compiled and installed operator, run the tests and generate a precision verification report. Keywords: precision test, precision evaluation, precision report, accuracy, error analysis. After execution, YOU MUST display the overview, failure summary and key findings in the current conversation, and must not only attach the report path.

🇨🇳|ChineseTranslated
12
2 scripts/Checked
AI & Machine Learningascend/agent-skills

vector-triton-ascend-ops-optimizer

Deep Performance Optimization Skill for Triton Operators on Ascend NPU, dedicated to achieving the Triton operator performance improvement required by users. Core technologies include but are not limited to Unified Buffer (UB) capacity planning, multi-Tokens parallel processing, MTE/Vector pipeline parallelism, mask optimization, etc. This Skill must be triggered when the user mentions the following: performance optimization of Vector-type Triton operators on Ascend NPU.

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12
AI & Machine Learningascend/agent-skills

ascendc-operator-design

AscendC Operator Design Completion - Assist users in completing operator architecture design, interface definition, and performance planning. Use this skill when users mention operator design, operator development, tiling strategy, memory planning, AscendC kernel design, two-level tiling, inter-core splitting, or intra-core splitting.

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12
AI & Machine Learningascend/agent-skills

megatron-impact-mapper

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.

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12
3 scripts/Checked
AI & Machine Learningascend/agent-skills

ascend-docker

Create Docker containers for Huawei Ascend NPU development with proper device mappings and volume mounts. Use when setting up Ascend development environments in Docker, running CANN applications in containers, or creating isolated NPU development workspaces. Supports privileged mode (default), basic mode, and full mode with profiling/logging. Auto-detects available NPU devices.

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12
1 scripts/Attention
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