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Dramatically reduces AI agents' context usage by sandboxing large tool outputs and indexing only relevant snippets into a searchable SQLite FTS5 (BM25) knowledge base, improving session continuity and privacy. Deploys cross-platform hooks and sandbox tools to cut context size by ~98% and avoid dumping raw logs into the model's window. ([github.com](https://github.com/mksglu/context-mode/blob/main/README.md?utm_source=openai))
Provides persistent, searchable memory for coding agents (Claude Code, Cursor, Gemini CLI, etc.), automatically capturing tool usage and session facts. Combines BM25, vector embeddings and a knowledge graph for hybrid retrieval, reducing token costs and re-explaining between sessions.
Provides a suite of Claude Code skills that guide the full academic pipeline—research, write, review, revise, and finalize—while enforcing integrity gates (citation verification, anti-hallucination checks) and keeping a human-in-the-loop workflow.
Builds a local structural knowledge graph of a codebase so AI coding assistants read only the minimal, relevant code during reviews and daily tasks—reducing tokens used while providing blast-radius impact analysis, incremental updates, and MCP integrations.
Audits and reduces token waste in LLM sessions by compressing verbose outputs, checkpointing before compaction, and restoring lost context. Runs fully locally with zero telemetry and provides a live token dashboard plus plugins for Claude Code, OpenClaw and Codex.
Provides AI coding agents with persistent memory inside an Obsidian vault—preserving session context, decisions, and notes across sessions. Integrates hooks/commands for Claude Code, Codex CLI, and Gemini CLI and optionally uses QMD for semantic recall; aimed at developer workflows.
Encodes product-management frameworks into reusable AI skills and slash-commands — 100+ skills across 9 plugins and chained workflows (e.g., /discover, /write-prd) that integrate with Claude Code/Cowork and other assistants to guide discovery, strategy, execution, and shipping.
Convenes 18 deliberately polarized AI personas to produce structured, multi-round deliberations on hard questions across multiple LLM providers. Key features: multi-provider auto-routing, enforced dissent/novelty rules, triad/panel modes and CLI integration for Claude Code/Codex. Good for high-stakes product, strategy, or safety decisions.
Real-time monitoring and control dashboard for Claude Code agents — tracks sessions, agent/subagent activity, tool calls, and live analytics. Local-first integration via Claude Code hooks, with Kanban/status board, MCP tool catalog, and web/desktop clients.
Generates production-ready App Store and Google Play screenshots from app metadata and style preferences using AI. Scaffolds a Next.js project, composes ad-style slides with localized/RTL support, and exports PNGs at all required Apple and Google resolutions.
Automatically converts codebases into structured, JSON-first CLI harnesses so LLMs and AI agents can reliably control desktop and server software; includes a CLI-Hub registry, demo harnesses, and agent plugins for one‑command generation and installation.
Terminal-first toolkit that automates bug bounty workflows — recon, hunting across 20 vulnerability classes, validation, and submission-ready report generation; runs as a Claude Code plugin or standalone CLI with support for free local AI providers (Ollama, Groq, DeepSeek).