Results for “temporal-memory”

Multi-tiered memory management (HOT/WARM/COLD) for context compaction. Invoke ONLY for explicit compaction events: post-`/compact` cleanup, MEMORY.md tier promotion, archive batch, or "trim my context". NOT for general recall (use deep-recall) or routine memory writes (use storage-router). Triggers: "compact memory", "promote to durable", "archive old context", "tier this".

Temporal interval algebra for reasoning about time relationships in planning and knowledge representation

Time (afag-time)

Temporal Data

Merges mature lessons from a domain memory file into its instruction file, preserving knowledge with minimal redundancy.

Transforms lessons learned into domain-organized memory instructions that persist across VS Code contexts, with global and workspace scopes.

Implements a continual learning loop for AI coding agents using hooks, two-tier memory (global and local), and automatic pattern detection to persist and apply learnings across sessions.

Save information to persistent memory for cross-session recall. Stores preferences, conventions, decisions, and context.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Persistent cross-session memory management. Enables agents to remember user preferences, project conventions, and past decisions across different sessions using a structured MEMORY.md index and topic files.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

通用记忆抽象接口。当定义记忆结构、记忆检索、记忆关联时调用此技能。

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

通用时间抽象接口。当定义时间维度、时序关系、时间演化时调用此技能。

Persistent long term memory for for continuity in ai sessions between providers and codegen tools.

Review reusable project knowledge and decide what belongs in project memory, notepad, or durable docs

Memory (aeaf-memory)

Memory (acaf-memory)

Memory (aaaf-memory)

clawhip × filesystem-offloaded memory

Capture durable project memory from work, debates, debugging discoveries, learned conventions, deferred options, and session outcomes. Load when the user says remember this, save this learning, record what happened, update project memory, or preserve context for future agents.

Record durable project decisions with rationale, alternatives, assumptions, status, and revisit triggers. Load when the user says record this decision, we decided, decision log, why did we choose, revisit this later, or capture architectural/process rationale.

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.

Transforms lessons learned into domain-organized memory instructions (global or workspace). Syntax: `/remember [>domain [scope]] lesson clue` where scope is `global` (default), `user`, `workspace`, or `ws`.

FREE — God-tier long-context memory for AI agents. Injects 500K-1M clean tokens, auto-summarizes with tone/intent preservation, compresses 14-turn history into 800 tokens.

Create and maintain TeamMember entities — humans and named AI personas that participate in the project with persistent identity, personality, and tiered memory. Use when adding a new persistent team-member (human or named AI), managing the name pool, scaffolding memory trees, or exporting/importing a team-member bundle. Replaces the deprecated actor-profile skill (DEC-20260422_0233-SpryTulip).

Single-skill wrapper for the 4-layer recall (durable memory → semantic DB → PostgreSQL → daily notes). Use BEFORE saying "I don't have context". Triggers: "search memory", "what do we know about X", "deep recall", "I don't remember".

Autonomous memory system for persistent learning across sessions. Automatically saves architectural decisions, bugfixes, patterns, and insights. Use to recall context from previous work and build institutional knowledge.

Persist decisions, preferences, and project state across sessions using structured memory types