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Found 27 Skills
Audit and prune bloated CLAUDE.md or AGENTS.md context files using evidence-based criteria from research on what actually helps coding agents. Use when a user asks to trim, audit, review, or improve their CLAUDE.md, AGENTS.md, or any repository context file for AI coding agents.
Load top-performing Shinka programs into agent context using `shinka.utils.load_programs_to_df`, and emit a compact Markdown bundle for iteration planning.
Expert skill for using OpenViking, the open-source context database for AI Agents that manages memory, resources, and skills via a filesystem paradigm.
Execute the implementation planning workflow and generate design artifacts using the plan template. Trigger phrase: "speckit plan".
Extract full context of the last task from the most recent parent session shown in the session lineage. Strategically uses sub-agents to avoid bloating your own context.
Design memory hierarchy with progressive loading for optimal context management. Use when organizing CLAUDE.md imports, implementing just-in-time context loading, or designing priming hierarchies for agents.
Execute the implementation planning workflow using the plan template to generate design artifacts.
Set up and manage a Memory Bank system for cross-session context continuity across AI coding agents. Use when the user mentions 'memory bank' with any action intent — setup, install, initialize, init, update, refresh, sync, status, check, read, show, review, display, or equivalents in any language (e.g. Turkish: kur, kurulum, güncelle, durumu, oku; German: einrichten, aktualisieren; Spanish: configurar, actualizar; French: installer, mettre à jour). Supports Claude Code, Cursor, Windsurf, Cline, GitHub Copilot, Roo Code, Aider, Antigravity, and OpenAI Codex.
Write, audit, and improve agent context files (AGENTS.md, CLAUDE.md) for AI coding agents. Use when creating or improving agent context for a codebase.
Use when starting work on any project to produce or update living documentation (TechStack.md, ProjectStructure.md) that bootstraps context for any AI agent session. Run before any feature work, or periodically to keep docs current.
Monitors context window health throughout a session and rides peak context quality for maximum output fidelity. Activates automatically after plan-interview and intent-framed-agent. Stays active through execution and hands off cleanly to simplify-and-harden and self-improvement when the wave completes naturally or exits via handoff. Use this skill whenever a multi-step agent task is underway and session continuity or context drift is a concern. Especially important for long-running tasks, complex refactors, or any work where degraded context would silently corrupt the output. Trigger even if the user doesn't say "context surfing" — if an agent task is running across multiple steps with intent and a plan already established, this skill is live.
Use when optimizing agent context, reducing token costs, implementing KV-cache optimization, or asking about "context optimization", "token reduction", "context limits", "observation masking", "context budgeting", "context partitioning"