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PythonReactSEOPDF

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30,841–30,864 sur 96,528

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GitHub

using-skillpack-maintenance

tachyon-beep

Use when maintaining, enhancing, or modifying existing Claude Code plugins - handles skills, commands, agents, hooks, and reference sheets through systematic domain analysis, structure review, behavioral testin...

GitHub

using-dynamic-architectures

tachyon-beep

Use when building networks that grow, prune, or adapt topology during training. Routes to continual learning, gradient isolation, modular composition, and lifecycle orchestration skills.

GitHub

using-system-archaeologist

tachyon-beep

Use when analyzing existing codebases to generate architecture documentation - coordinates subagent-driven exploration with mandatory workspace structure, validation gates, and pressure-resistant workflows

GitHub

using-software-engineering

tachyon-beep

Use when facing complex engineering challenges that require systematic methodology - horrible bugs, safe refactoring, code review, production incidents, technical debt decisions, or building confidence in unfam...

GitHub

using-system-architect

tachyon-beep

Use when you have architecture documentation from system-archaeologist and need critical assessment, refactoring recommendations, or improvement prioritization - routes to appropriate architect specialist skill...

GitHub

sme-agent-protocol

tachyon-beep

Mandatory protocol for all SME (Subject Matter Expert) agents. Defines fact-finding requirements, output contracts, confidence/risk assessment, and qualification of advice.

GitHub

using-quality-engineering

tachyon-beep

Use when user asks about E2E testing, performance testing, chaos engineering, test automation, flaky tests, test data management, or quality practices - routes to specialist reference sheets with deep expertise...

GitHub

retail-agent-customizer

lavinigam-gcp

Customize the retail agent for different use cases. Use when adapting for different business types, industries, or output formats, or when modifying prompts, adding verticals, or changing the analysis focus.

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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