技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v0.1.0
统计：⭐ 0 · 228 · 1 current installs · 1 all-time installs
⭐ 0
安装量（当前） 1
🛡 VirusTotal ：良性 · OpenClaw ：可疑
Package：404-unknow/engram-evomap
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：可疑
OpenClaw 评估
The skill appears to implement a coherent long‑term memory store, but it will send session history to an LLM, persist distilled capsules to disk, download a local model at runtime, and contains seed capsules that recommend insecure commands — these behaviors warrant caution.
目的
Name/description (AEIF long-term memory for agents) match the code and instructions: it vectorizes queries, stores AEIF capsules in SQLite, and provides consult/commit/list commands. Requiring node is appropriate; no unrelated credentials or binaries are requested.
说明范围
SKILL.md tells the agent to auto-consult on error signals and to auto-commit distilled experiences. The actual implementation will send recent session history to an LLM (GeneProcessor.distill / VerificationEngine.selfReflect) and then store resulting capsules (rawPayload) in a local DB. That means potentially sensitive conversation content will be transmitted to whatever LLM client the agent provides and may be persisted locally. The skill doe…
安装机制
There is no install spec in the metadata (instruction-only), but the packaged code depends on @xenova/transformers and at runtime will download a transformer model (all‑MiniLM‑L6‑v2) into ~/.engram_cache. Runtime model downloads and writing a cache directory are notable (network activity and disk writes), but are expected for an offline semantic engine.
证书
The skill requests no explicit environment variables or credentials, which is consistent. However, it uses process.env and the agent's provided llmClient to call external LLM(s) for distillation and verification. That implies session content and derived capsules will be released to the agent's LLM provider and stored locally. The skill also writes a DB (data/engram.db) and cache (~/.engram_cache) by default — these file writes are reasonable f…
持久
always is false; the skill isn't force-enabled. It does persist data (SQLite DB) and cache model files under the user's directories and spawns worker threads. Autonomous invocation is allowed (platform default), which combined with the auto-commit/auto-intercept rules increases the chance that content will be sent to an LLM and stored without an extra explicit user action.
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Engram Evomap - Long Term AI Memory」。简介：The AEIF-based long-term memory hub for AI Agents to prevent repeating bugs.。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/404-unknow/engram-evomap/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: engram-evomap
description: The AEIF-based long-term memory hub for AI Agents to prevent repeating bugs.
metadata:
openclaw:
requires:
env: []
bins:
- node
cliHelp: |
npx engram --help
Usage: !exp consult <query> | !exp commit | !exp list
---
# 🧬 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.