2,023 results in Skills, Workflows, Hooks, Identity · page 19 of 85
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constitutional-ai
Anthropic's method for training harmless AI through self-improvement. Two-phase approach - supervised learning with self-critique/revision, then RLAIF (RL from AI Feedback). Use for safety alignment, reducing harmful outputs without human labels. Powers Claude's safety system.
Create SEO-optimized marketing content with consistent brand voice. Includes brand voice analyzer, SEO optimizer, content frameworks, and social media templates. Use when writing blog posts, creating social media content, analyzing brand voice, optimizing SEO, planning content calendars, or when user mentions content creation, brand voice, SEO optimization, social media marketing, or content strategy.
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
Primes Claude with comprehensive project understanding by loading repository structure, setting development context, establishing project goals, and defining collaboration parameters.
Provides a systematic approach to priming Claude Code with comprehensive project context through specialized commands for different project scenarios and development contexts.
Real-time browser visualization of Claude Code's context window and subagent/tool execution as a git-graph timeline. Opens http://localhost:7878 on SessionStart with a vertical timeline (most recent on top), one column per agent (main + subagents branching from their Task tool call). Tool calls are color-coded by type (Read=green, Edit/Write=orange, Bash=red, Grep/Glob=cyan, Task=purple, Web=yellow, MCP=gray). Right sidebar shows context-window usage (tokens/200K) with cache_read/cache_creation/input/output breakdown plus per-subagent mini-context. Reads ~/.claude/projects/<encoded-cwd>/<session_id>.jsonl directly — no data replication, no network calls. Pure stdlib Python, zero pip dependencies. Persistent daemon HTTP server on port 7878 (auto-fallback 7879-7888 if busy; override with CONTEXT_TIMELINE_PORT env var). Watchdog auto-shutdown after 1h of inactivity. Disable browser auto-open with CONTEXT_TIMELINE_NO_BROWSER=1. Manual shutdown: python3 .claude/hooks/context-timeline.py --shutdown
Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context engineering, long context.
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.