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Engrm Delivery Review

作者 dr12hes · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install engrm-delivery-review
功能描述
Use Engrm to compare what was asked, what was promised, and what evidence suggests was actually delivered.
使用说明 (SKILL.md)

Engrm Delivery Review

Use this skill when the user wants to know whether the agent really delivered what it claimed, or when a session may have drifted from the original brief.

Before you start

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

If Engrm is not available, say that Delivery Review cannot use Engrm on this machine yet and continue without inventing setup or shell instructions.

Command guardrails

Do not invent Engrm CLI commands such as engrm search, engrm save, or engrm timeline.

Use Delivery Review as an Engrm workflow and memory discipline, not as a made-up shell command surface.

What this skill is for

  • Compare the brief, plan, and decisions against the session outcome.
  • Spot partial delivery, scope drift, or refactor-heavy sessions.
  • Surface weak decision trails and likely follow-up risk.
  • Turn sessions into accountable project history instead of vague timelines.

When to use it

Use this skill when:

  • the agent says work is done and confidence needs verifying
  • the user suspects partial delivery
  • the session touched many files but produced unclear outcome evidence
  • later work reopened an area that was supposedly finished
  • a refactor may have displaced the original goal

Delivery Review questions

  • What was the user actually asking for?
  • What plan did the agent commit to?
  • What decisions were captured?
  • What evidence of delivery exists?
  • What still looks missing, weak, or reopened?

Review lenses

Look for these patterns:

  • delivered as planned
  • partially delivered
  • scope drifted
  • refactor instead of delivery
  • built without a clear decision trail
  • reopened after completion

Strong evidence

Good evidence includes:

  • concrete implementation activity tied to the brief
  • decisions followed by matching changes
  • later sessions not needing to reopen the same work
  • clear memory entries that explain why the work was done

Weak evidence includes:

  • lots of movement with little outcome clarity
  • vague completion language
  • decisions with no matching implementation trail
  • later sessions repairing or redoing the same area

What to save after review

Save:

  • the real outcome
  • the main gap or drift
  • the lesson future sessions should know first

Do not save a flattering summary if the evidence is mixed. Prefer truthful, useful review over optimistic narration.

安全使用建议
This skill is low-risk: it’s a checklist/workflow for reviewing session delivery and only works if Engrm is already connected. Before installing, confirm you trust the Engrm integration (the skill relies on it but does not set it up), and be aware that the review will operate over whatever session history/memory the agent has access to — avoid exposing new sensitive data to the agent during review. Because it’s instruction-only and requests no credentials, there is no additional installation footprint or network endpoint to vet.
功能分析
Type: OpenClaw Skill Name: engrm-delivery-review Version: 0.1.0 The skill bundle contains instructions for an AI agent to perform project delivery reviews and identify scope drift using a tool called Engrm. The files (SKILL.md, README.md) focus entirely on workflow discipline and session accountability without any executable code, suspicious shell commands, or requests for sensitive data.
能力评估
Purpose & Capability
Name/description match the instructions: the skill is explicitly a review workflow that uses Engrm if already present. It does not request unrelated credentials, binaries, or files.
Instruction Scope
SKILL.md confines behavior to using Engrm when available, forbids inventing CLI commands or performing setup, and focuses on comparing brief/plan/decisions/evidence. It does not instruct reading unrelated system files or exfiltrating data.
Install Mechanism
No install spec and no code files — instruction-only skill with no downloads or filesystem writes.
Credentials
Requires no environment variables, no credentials, and no config paths. The only external dependency is the presence of Engrm in the environment, which is explicitly referenced.
Persistence & Privilege
always is false and the skill does not request elevated or persistent privileges. It does not modify other skills or system settings.
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-delivery-review
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /engrm-delivery-review 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 delivery review skill release
元数据
Slug engrm-delivery-review
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 Delivery Review 是什么?

Use Engrm to compare what was asked, what was promised, and what evidence suggests was actually delivered. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 163 次。

如何安装 Engrm Delivery Review?

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

Engrm Delivery Review 是免费的吗?

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

Engrm Delivery Review 支持哪些平台?

Engrm Delivery Review 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 Delivery Review?

由 dr12hes(@dr12hes)开发并维护,当前版本 v0.1.0。

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