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在 OpenClaw 中安装
/install nm-tome-research
功能描述
Multi-source research across code, discourse, and academic channels
安全使用建议
This skill's workflow fits its description, but the SKILL.md assumes you have a Python runtime, a local 'tome' package providing many modules, and an 'Agent' dispatch tool — none of which are declared in the metadata. Before installing/using: (1) confirm your agent/runtime provides the 'tome' package and the Agent tool or add an explicit install step; (2) be aware the skill will write session files to your current working directory (docs/research/...), so run it in an appropriate or isolated workspace; (3) if you don't want automatic filesystem writes, request a dry-run or adjust the save path; (4) no credentials are requested by the skill, but lack of declared dependencies may cause silent failures — verify prerequisites first. I have medium confidence because the issues look like omissions/assumptions rather than clearly malicious intent; providing the runtime dependency list or an install spec would raise confidence to benign.
功能分析
Type: OpenClaw Skill
Name: nm-tome-research
Version: 1.0.0
The skill is a research orchestrator designed to manage a multi-step workflow including domain classification, research planning, and parallel agent dispatching using the 'tome' library. The instructions in SKILL.md define a legitimate process for synthesizing findings from various sources (code, discourse, academic) and saving formatted reports to the local filesystem (docs/research/). No evidence of malicious intent, data exfiltration, or prompt injection was found in the provided files.
能力评估
Purpose & Capability
The SKILL.md's workflow (domain classification, dispatching code/discourse/academic agents, synthesizing findings, saving reports) matches the declared purpose of multi-source research. However the instructions assume a local Python package named 'tome' (modules like tome.scripts.*, tome.session, tome.synthesis, tome.output) and an 'Agent' tool for dispatching parallel agents; those runtime dependencies are not declared in the skill metadata.
Instruction Scope
Instructions include executable Python snippets, create a SessionManager using Path.cwd(), and save reports to docs/research/{session.id}-{slug}.md. That requires filesystem write access and a Python runtime with the referenced modules. The SKILL.md does not instruct exfiltration or access unrelated credentials, but it does assume access to local project files and ability to persist session state.
Install Mechanism
This is instruction-only with no install spec and no code files, so there is no installer risk. However the lack of an install step means the SKILL.md's Python modules and tools must already exist in the runtime; the metadata does not document how to obtain them.
Credentials
The skill requests no environment variables or credentials, which is proportionate. That said, it implicitly needs filesystem access and a Python environment with the 'tome' package and an 'Agent' tool; these implicit requirements are not declared, which is an omission the user should be aware of.
Persistence & Privilege
always:false and no install hooks are present. The skill instructs saving session state to the local docs/research/ path (its own workspace), which is a reasonable behavior for a research orchestrator and does not request elevated platform privileges or attempt to modify other skills.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install nm-tome-research - 安装完成后,直接呼叫该 Skill 的名称或使用
/nm-tome-research触发 - 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
v1.0.0
Research skill orchestrates multi-source investigations with structured agent coordination and synthesis.
- Runs a session workflow: domain classification, research planning, parallel agent dispatch, synthesis, and reporting.
- Supports code, discourse, academic, and TRIZ channels; always uses code/discourse, conditionally adds others.
- Automates merging and ranking of findings across sources, then outputs a formatted report.
- Provides error handling: partial results persist, empty synthesis is reported clearly, and manual fallback advised if all agents fail.
- Saves all research states and results; output format customizable (full report, brief, or transcript).
- Users receive summaries and suggestions for next research steps.
元数据
常见问题
Nm Tome Research 是什么?
Multi-source research across code, discourse, and academic channels. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。
如何安装 Nm Tome Research?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install nm-tome-research」即可一键安装,无需额外配置。
Nm Tome Research 是免费的吗?
是的,Nm Tome Research 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Nm Tome Research 支持哪些平台?
Nm Tome Research 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 Nm Tome Research?
由 athola(@athola)开发并维护,当前版本 v1.0.0。
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