massive-context-mcp
Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.
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535 skills found
Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.
Ensures adherence to standardized global documentation patterns for technical projects, maintaining consistency across repositories and agent-based workflows.
Generate absurdly thorough, professional README.md files for any project, covering local development, system architecture, and deployment instructions.
Systematic security assessment using STRIDE threat modeling, OWASP top 10 review, and secure coding practices for code, architecture, and infrastructure.
Analyze product performance using KPI frameworks, cohort analysis, and funnel metrics to drive growth, retention, and feature adoption.
Universal MCP client for connecting to any MCP server with progressive disclosure. Wraps MCP servers as skills to prevent context window bloat from tool definitions. Use for Zapier, GitHub, sequential thinking, and file operations.
Automated security vulnerability scanner implementing OWASP Top 10 testing for SAST/DAST, dependency auditing, and auth/authorization validation in CI/CD pipelines.
GitHub operations via gh CLI. Use for repository inspection, issues, PRs, releases, and deep codebase analysis including cloning for architectural insights.
Conduct thorough dependency audits to identify redundant code, unused features, and improper usage patterns. Ensures project modularity by leveraging existing dependencies instead of reinventing functionality.
Analyze Claude Code session history to identify inefficiencies, optimize token usage, and suggest workflow improvements.
Advanced Python security vulnerability scanner for Flask, Django, and FastAPI projects. Audits OWASP Top 10, dependencies, hardcoded secrets, and framework-specific flaws.
Develop, test, sign, and publish governance plugins for Memoria using Rhai or gRPC runtimes. Manage the full plugin lifecycle from scaffolding to activation.