memov
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
314 skills found
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Framework for building professional competitive landscape decks, including market positioning, peer benchmarking, and strategic synthesis for finance professionals.
Generate professional Product Requirements Documents (PRD) and structure features for autonomous development cycles.
Comprehensive toolkit for graph creation, network analysis, and visualization in Python. Ideal for analyzing relationships, centrality, community detection, and synthetic network generation across diverse research domains.
Systematic security assessment using STRIDE threat modeling, OWASP top 10 review, and secure coding practices for code, architecture, and infrastructure.
Automate GitHub issue triage by analyzing reports against the codebase, verifying technical claims, and providing expert-driven responses to resolve invalid issues.
Interprets Culture Index (CI) surveys and behavioral profiles. Analyzes team composition, burnout risk, and hiring profiles using data-driven trait assessment.
UI component patterns and touch input handling for M5Stack Tab5 applications using M5GFX and LVGL.
Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.
Resume a paused experimental loop by restoring branch context, loading configuration, reading history, and identifying optimization patterns for continued iteration.
Production-ready Go development support: concurrency patterns, idiomatic error handling, interface design, testing with testify, and Go best practices for scalable backend services.
Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.