一键导入
graphiti-temporal
Temporal context graph for agent memory — track entity relationships and state changes over time
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Temporal context graph for agent memory — track entity relationships and state changes over time
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Onboard a new client/company onto this platform's real Agentic OS: create the company record, scan its websites/repos, auto-provision specialist agents, activate its 24x7 agency runtime, and know exactly which "OS" building blocks (memory, integrations, dashboard) already exist versus which are roadmap gaps. ADAPTED FROM: a third-party giveaway skill ("agentic-os-installer" by Gennaro Santoro / Operations Heroes) that described a generic vault + Google-suite + skill-pack installer. That skill's product (Obsidian vault, Gmail/Calendar/ Drive wiring, "skill packs") does not exist in this repo and its promotional content (Skool community link) does not belong here. This is a clean-room rewrite that keeps the useful idea — "stand up a working agency OS for a client from a short checklist" — and maps every step to the real module that already implements it in this codebase, per CLAUDE.md architecture rules.
Agile sprint planning, velocity tracking, and burndown metrics for agent-managed projects
Initiative-level portfolio management with dependency tracking and milestone coordination
AI-assisted engineering impact analysis — productivity metrics and code quality insights
Cross-harness agent patterns — standardize agent execution across different coding assistants
Andrej Karpathy's coding guidelines for AI agents — concise, correct, and well-tested code
| name | graphiti-temporal |
| description | Temporal context graph for agent memory — track entity relationships and state changes over time |
Inspired by: Graphiti — temporal context graphs for AI agents
Purpose: Integrate Graphiti's temporal knowledge graph patterns into local-llm-server's agent memory and context management.
Graphiti builds temporal context graphs (evolving knowledge graphs that track how facts change over time):
Unlike traditional RAG (flat chunks), Graphiti gives agents rich, structured context that evolves with each interaction.
Track agent decisions and outcomes:
class AgentContextGraph:
def add_interaction(self, timestamp, agent_id, action):
"""Record agent action with temporal metadata"""
def query_at_time(self, entity, timestamp):
"""Query what was true at specific time"""
Track which agents worked on which tasks with temporal awareness.
Query across relationships with SQL:
SELECT entity, fact, timestamp FROM context_graph
WHERE entity LIKE 'test_%'
AND fact LIKE 'status:failed'
ORDER BY timestamp DESC;
CREATE TABLE temporal_context (
id TEXT PRIMARY KEY,
entity TEXT NOT NULL,
fact TEXT NOT NULL,
timestamp DATETIME NOT NULL,
provenance TEXT,
agent_id TEXT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
);
CREATE INDEX idx_entity_time ON temporal_context(entity, timestamp DESC);
services/temporal_context.py — temporal graph implementationdb/temporal_store.py — SQLite storagetests/test_temporal_context.py — tests