← 返回 Skills 市场
dr12hes

Engrm Memory

作者 dr12hes · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
162
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install engrm-memory
功能描述
Use Engrm memory deliberately before coding, during coding, and when saving reusable lessons.
使用说明 (SKILL.md)

Engrm Memory

Use this skill when the user is working on an existing codebase and continuity matters more than a cold start.

Before you start

Use Engrm only if it is already connected and available in the current environment.

If Engrm is not available, say that Engrm memory is not connected on this machine and continue without inventing fallback commands or fake setup steps.

Command guardrails

Do not invent Engrm CLI commands like:

  • engrm search
  • engrm save
  • engrm timeline

Those are not normal Engrm CLI commands.

Memory search, timeline, save, recent activity, and stats are Engrm tool/workflow capabilities, not generic shell commands.

What this skill is for

  • Pull relevant prior knowledge into the current session.
  • Reuse past decisions, fixes, and discoveries before repeating work.
  • Save new knowledge when the session produces something worth carrying forward.
  • Make multi-device and multi-agent memory actually useful instead of passive.

When to use Engrm first

Use Engrm before coding when:

  • the user is resuming work after a break
  • a project or subsystem looks familiar
  • the task touches a bug, auth flow, deployment path, or refactor area that may have been handled before
  • the session starts on a different machine or with a different coding agent

Use Engrm during coding when:

  • the work starts drifting
  • you need to confirm an earlier decision
  • you suspect the same issue has already been solved elsewhere

Use Engrm after coding when:

  • a useful decision was made
  • a bugfix or pattern is likely to recur
  • the session discovered a real lesson that future work should start with

Default Engrm workflow

  1. Start by checking recent activity or searching relevant memory.
  2. Pull timeline or session context if the area has recent churn.
  3. Apply prior decisions before changing code.
  4. Save only high-signal outcomes, not every trivial step.

Good Engrm questions

  • What did we already learn about this area?
  • Was there an earlier decision for this approach?
  • Did a previous session touch the same files or subsystem?
  • Is there a recent bugfix or security note I should reuse?

Save high-signal memories

Prefer saving:

  • durable decisions
  • bugfixes with clear cause and resolution
  • discoveries that unblock later sessions
  • patterns worth reusing across projects

Avoid saving:

  • obvious implementation details
  • noisy or temporary dead ends
  • generic filler that will pollute retrieval later

What success looks like

The agent starts informed, reuses real project memory, and leaves behind a small number of valuable observations that improve the next session.

安全使用建议
This skill is a set of usage rules for an external memory service (Engrm) and is internally consistent. Before installing or using it, confirm that you actually have a trusted Engrm integration available in your environment (the skill assumes an existing connection and forbids inventing access methods). Consider privacy implications of saving project memories — ensure saved items don't contain secrets or proprietary data, and verify which agent or service will perform the actual memory reads/writes. If your environment lacks Engrm, the skill advises to continue without attempting to fabricate access.
功能分析
Type: OpenClaw Skill Name: engrm-memory Version: 0.1.0 The skill bundle contains only documentation and behavioral instructions for an AI agent to interact with a memory tool called 'Engrm'. It lacks any executable code, network requests, or malicious prompt injections. Notably, SKILL.md includes command guardrails that specifically instruct the agent not to invent or execute unauthorized shell commands.
能力评估
Purpose & Capability
Name and description match the instructions: the skill guides use of an external memory system (Engrm). It requests no unrelated binaries, env vars, or config paths — nothing appears extraneous for this purpose.
Instruction Scope
SKILL.md confines itself to recommending when to read or save memory and explicitly forbids inventing Engrm CLI commands or fake setup steps. It does not instruct reading arbitrary files, exfiltrating data, or calling unexpected endpoints. It relies on Engrm being available but does not describe any out-of-scope data collection.
Install Mechanism
No install spec or code files — instruction-only skill, so nothing is written to disk or downloaded.
Credentials
No environment variables, credentials, or config paths are requested. This is proportional for a guidance-only skill that delegates actual memory access to existing infrastructure.
Persistence & Privilege
always is false and the skill does not request elevated or permanent platform privileges. Normal autonomous invocation is allowed (platform default) but the skill itself does not expand privilege.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install engrm-memory
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /engrm-memory 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
Initial Engrm memory skill release
元数据
Slug engrm-memory
版本 0.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Engrm Memory 是什么?

Use Engrm memory deliberately before coding, during coding, and when saving reusable lessons. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 162 次。

如何安装 Engrm Memory?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install engrm-memory」即可一键安装,无需额外配置。

Engrm Memory 是免费的吗?

是的,Engrm Memory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Engrm Memory 支持哪些平台?

Engrm Memory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Engrm Memory?

由 dr12hes(@dr12hes)开发并维护,当前版本 v0.1.0。

💬 留言讨论