Results for “cognition”

Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, implementing the dialectic chat endpoint for AI agents, or wiring Honcho into bot frameworks (nanobot, openclaw, picoclaw, etc).

Build a library of metacognitive prompts targeting planning, monitoring, or evaluation for a specific task. Use when developing students' thinking-about-thinking during independent work.

Builds a personal knowledge base for capturing and retrieving understanding, with structured namespaces for concepts, tools, patterns, and references.

Capture conversations and decisions into structured Notion pages for easy reuse as wiki entries, how-tos, decisions, or FAQs with proper linking.

Use before starting any new work to check for existing knowledge. This skill provides a systematic search and retrieval process for finding relevant knowledge from memory systems (PARA, Gigabrain, OpenStinger, existing skills) before starting work, preventing redundant effort and leveraging prior learning.

Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity.

Simulates a multi-perspective deliberation council to explore complex questions, decisions, or creative challenges from diverse thinking archetypes.

Stores, retrieves, and curates persistent facts in a structured memory map, distinguishing between user facts and reference text.

Applies behavioral science and persuasion frameworks to marketing. Use when the user requests 'cognitive bias', 'loss aversion', 'social proof', 'scarcity', 'Cialdini', or 'persuasion framework'.

Canonical kip knowledge-store patterns for any process or agent: recall prior facts before work, assert decisions/gate outcomes/rejections as structured facts after work, resolve entities with explicit --model sonnet, and invoke the CLI Windows-safely via node packages/kip-sdk/dist/cli/kip.js when kip is not on PATH.

Analyze any text to extract a cognitive fingerprint across 12 dimensions, revealing reasoning patterns, decision styles, and thinking signatures.

Forces unrelated concepts together to spark novel solutions and emergent properties.

当需要将个人知识或经验转化为商业机会，或希望建立有意义的个人发展路径时

Captures notes locally, organizes them by topic and project, and retrieves relevant notes on demand, including meeting preparation and idea synthesis.

Designs persistent memory architectures for AI agents, covering cross-session knowledge retention, entity tracking, temporal validity, graph/vector retrieval, and memory consolidation.

Manage a multi-layered knowledge system for ingesting, organizing, syncing, and retrieving knowledge across local files, MCP memory, vector stores, and Git repos.

Persists and recalls agent knowledge across sessions using four approaches: static KB, company wiki, persistent memory, and session brain.

Design structured perspective-taking activities with anti-projection guardrails. Develops genuine understanding of complexity across history, social sciences, and literature — not performed empathy.

当意识到自己处于迷茫、例行公事或心流等不同生活状态，并希望主动管理而非被动承受时

Use before any complex or ambiguous task where the path forward is unclear. For breaking down multi-step problems, choosing between approaches, clarifying vague requirements, identifying hidden assumptions, planning before building, and preventing costly mistakes from starting in the wrong direction. Activate when user says "how should I approach this", "what's the best way to", "I'm not sure how to", or presents a problem without a clear solution.

当需要主动从海量信息中寻找能带来深刻启发、挑战现有认知或激发好奇心的新想法时

Coordinates four reasoning skills and an agent for structured thinking, problem solving, creative ideation, and learning.

Composite skill — query, capture, improve, and persist knowledge in one workflow. Chains recall (RAG query) → sync-memories (write durable note) → rag-curate (improve weak retrievals) → handoff (durable snapshot if session-ending). Use when the work involves "what did we decide", "remember this", "save where we are", or any closing checkpoint.

Audits decisions and situations for operating psychological biases using Munger's 25 tendencies framework, producing a structured analysis with countermeasures.

当观察到或经历某种极端转化现象，或试图主动促成根本性观念转变时

当个人感到迷茫，不确定自己真正想要什么，或发现当前追求无法带来深层满足时，调用此模型来探索和澄清内在真实欲望

Diagnose and fix retention problems using the Fogg Behavior Model (B=MAP), covering motivation, ability, prompts, and tiny habits.

Design a sequence where students compare AI's handling of the same question across disciplines, developing a mental model of where AI is reliable vs. distorting based on knowledge type.

Think like a human. Reason, plan, adapt, create, and know your limits.

Brainstorming Skill

Design metacognitive checkpoints that prevent AI-assisted learning from bypassing genuine understanding. Use when students use AI tools and may overestimate their own comprehension.

Prepare meeting materials by pulling context from Notion, tailoring agendas and pre-reads, and enriching with research.

Personal knowledge base powered by Ensue for capturing and retrieving understanding. Use when user wants to save knowledge, recall what they know, manage their toolbox, or build on past learnings. Triggers on "save this", "remember", "what do I know about", "add to toolbox", "my notes on", "store this concept".

Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.

当遇到令人情绪激动或陷入僵局的情境，需要跳出固有反应模式以做出更优决策时