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Implements a Manus-style, file-backed planning workflow for AI agents using a three-file Markdown pattern (task_plan.md, findings.md, progress.md) to persist plans, findings and session logs—reducing context drift and enabling session recovery. Adds IDE/CLI hooks to re-read plans and verify completion.
Provides a Python API, CLI, and agent skill to programmatically access Google NotebookLM — exposing features the web UI omits (batch imports/exports, PPTX slides, mind‑map JSON) and integrating with LLM agents like Claude Code and Codex.
Provides a set of versioned "skills" that codify UI design standards and automated checks for design engineers and AI agents. Includes a CLI to discover, install, and run skills like baseline UI rules, accessibility fixes, motion-performance tuning, and metadata corrections.
Runs an autonomous agent loop that uses AI coding tools (Amp or Claude Code) to implement PRD user stories iteratively, persisting context via git history, progress.txt and prd.json; designed for small, CI-backed tasks.
Compresses any context sent to LLMs (tool outputs, DB reads, RAG results, files, logs) to cut tokens by ~70–95% while preserving reversible originals; runs as a proxy or Python/TypeScript SDK with integrations for common agent frameworks.
Enables Pi to delegate tasks to focused child agents for code review, parallel audits, background jobs, and saved workflows. Supports foreground and background runs, session artifacts, worktree isolation, and built-in role agents to simplify orchestration.
Provides a comprehensive, security-first guide and template library for using Claude Code — from core concepts and agentic workflows to production hardening. Includes threat DB (CVE mappings), 219 templates, 271-question quiz, and interactive diagrams.
Teams-first orchestration layer for Claude Code that runs, coordinates, and parallelizes multi-agent workflows from the CLI/tmux. Features team pipelines, skill extraction, provider adapters (Codex/Gemini), and realtime HUD for developer-focused automation.
Generates daily LLM-powered decision dashboards for A/H/US stocks by combining multi-source market data, real-time news, technical signals and agent-style strategy reasoning; deploys via GitHub Actions or Docker and pushes reports to multiple channels.
Teaches LLMs to detect and remove “AI tells” from prose using curated phrase/structure lists, before/after examples, and a 5‑dimension scoring rubric. Delivered as a reusable skill (SKILL.md + reference files) designed to plug into Claude or any LLM workflow for automated style sanitization.