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Android data layer implementation guide. Provides comprehensive patterns for Room Database (Entity, DAO, Migration), DataStore (Preferences), Repository layer design, and common pitfalls. Use when implementing local data storage, cache strategies, or data source integration in Android projects.
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Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
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Self-tuning question sensitivity + developer psychographic for gstack (v1: observational). Review which AskUserQuestion prompts fire across gstack skills, set per-question preferences (never-ask / always-ask / ask-only-for-one-way), inspect the dual-track profile (what you declared vs what your behavior suggests), and enable/disable question tuning. Conversational interface — no CLI syntax required. Use when asked to "tune questions", "stop asking me that", "too many questions", "show my profile", "what questions have I been asked", "show my vibe", "developer profile", or "turn off question tuning". (gstack) Proactively suggest when the user says the same gstack question has come up before, or when they explicitly override a recommendation for the Nth time.
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Compress bloated project or global memory while preserving decisions, rationale, revisit triggers, provenance, and active user preferences. Load when memory exceeds budget, global memory is too large, session logs are repetitive, or before appending to an over-budget memory file.
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Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
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Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruning, energy windows, conformer count, and force-field choice. Use when preparing 3D ligands for docking, generating descriptor input for 3D QSAR, or sampling macrocycle/peptide conformational ensembles.
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The Matrx user settings system (SettingsShell, useSetting, tab registry). Use when adding a preference or settings tab, binding a Redux slice to settings, wiring a settings deep link, or touching features/settings, components/official/settings, or components/user-preferences.
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Decides where a standing rule lives and builds the config Claude reads before work — CLAUDE.md, AGENTS.md, Project instructions and knowledge files, profile preferences, .claude/rules and agents, hooks, .mcp.json. Trigger on 'where should this rule live', 'set up a Claude Project', 'write or trim my CLAUDE.md', 'my rules get ignored', 'audit my setup for bloat or stale status', 'cut my CLAUDE.md token cost', 'add what we learned to CLAUDE.md', or rigwright (place, build, audit, learn, slim, refresh). Permissions, hook safety and config maps are gatewarden's; skills, skillwright's; unattended work, agentwright's; a block's wording, promptwright's.
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Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
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Automatic architecture video editing workflow with self-learning preferences
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Generates a comprehensive and best-practice-oriented .editorconfig file based on project analysis and user preferences.
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Interactive onboarding wizard that generates agency.config.json for any B2B agency. Asks structured questions about the agency, services, ICP, tools, outreach preferences, and CRM setup. Outputs a complete config file.
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