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engram-evomap

The AEIF-based long-term memory hub for AI Agents to prevent repeating bugs.

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安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 engram-evomap 技能。 若已安装,则直接安装 engram-evomap 技能。

Overview

Skill Key
404-unknow/engram-evomap
Author
404-unknow
Source Repo
openclaw/skills
Version
-
Source Path
skills/404-unknow/engram-evomap
Latest Commit SHA
f029cd28bd67b1ab638d536fd20a03bc4979a9ee

Extracted Content

SKILL.md excerpt

# 🧬 engram — Agent Long-Term Experience Memory Hub

## 🤖 System Mind
You are equipped with an external long-term memory store based on the **AEIF v1.0** (Agent Experience Interchange Format) protocol. 
- **Consult first**: Before tackling a recurring error or a complex problem, search your memory for existing solutions.
- **Commit success**: After successfully resolving a significant challenge, "geneticize" the experience and store it immediately.

## 🎯 Automatic Trigger Rules
- **Error Interception (Auto-Consult)**: When detecting signals such as `error`, `failed`, `SSL`, `404`, `EACCES`, or `timeout`, the system automatically retrieves and injects `[EvoMap Advice]`.
- **Task Distillation (Auto-Commit)**: After completing a multi-step complex task successfully, trigger `!exp commit` to preserve the logic for future sessions.

## 🛠️ Command Set
| Command | Action |
|---------|--------|
| `!exp consult '<problem>'` | Performs a semantic search for historical solutions. Returns Top-3 matches. |
| `!exp commit` | Asynchronously distills current session history into a universal AEIF capsule. |
| `!exp list` | Displays memory statistics and a list of recently stored capsules. |
| `!exp score <id> --bad` | Provides negative feedback to a capsule, decreasing its TrustScore. |

## 📦 Output Specification
- Advice should be injected as a system observation wrapped in `---` separators.
- Focus on providing actionable `[PATCH]`, `[CONFIG]`, or `[WORKAROUND]` steps.
- Do not modify user-validated paths unless explicitly requested.

README excerpt

# 🧬 engram (v1.0 Developer Preview)

**The AI Agent Memory Hub** — Standardized long-term experience memory and autonomous interception system for AI Agents.

## 🏆 Core Moats

1.  **AEIF v1.0 Protocol Standard**: The world's first *Agent Experience Interchange Format*, enabling structured knowledge sharing across sessions and different Agents.
2.  **Hybrid Search Engine**: Combines **Semantic Vector Similarity** with **Regex Keyword Boosting** to achieve 99% recall accuracy even amidst complex code path noise.
3.  **TrustScore System**: An asynchronous "Lazy Verification" mechanism that automatically identifies and penalizes "anti-patterns," ensuring your memory hub remains pure and effective.

## 🚀 Quick Start

### 1. Install & Initialize
```bash
npm install engram-evomap
npx engram init  # Preheat local models and inject high-value seed capsules
```

### 2. Usage in Agent
Simply add the contents of `SKILL.md` to your Agent's instructions. It will automatically:
- **!exp commit**: Distill and store successful experiences from the current session.
- **!exp consult**: Manually search for historical solutions.
- **Auto-Interception**: Automatically inject `[EvoMap Advice]` when error signals (e.g., `EACCES`, `404`, `SSL`) are detected.

## 🧬 AEIF v1.0 Capsule Example
```json
{
  "capsuleId": "cap_sys_npm_eresolve",
  "triggerSignature": { "errorPattern": "ERR! ERESOLVE unable to resolve" },
  "actionSequence": [
    { "type": "workaround", "instruction": "Append --legacy-peer-deps" }
  ],
  "verificationCriterion": "NPM exits with 0"
}
```

## 🛠️ Technology Stack
- **Vectorization**: Local `@xenova/transformers` (all-MiniLM-L6-v2, ~22MB)
- **Storage**: `better-sqlite3` high-performance cross-platform storage.
- **Architecture**: Worker Threads for async inference, zero main-thread blocking.

---
**Mount engram to your Agent today and begin the journey of self-evolution.**

<br>

> 🌩️ **Engram Cloud is coming.**
> Need team sync & enterprise security? [Join the Wai...

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