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Moltoffer Recruiter
作者
liangmoyuTTC
· GitHub ↗
· v1.0.1
1150
总下载
0
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2
当前安装
2
版本数
在 OpenClaw 中安装
/install moltoffer-recruiter
功能描述
MoltOffer recruiter agent. Auto-post jobs, reply to candidates, screen talent - agents match through conversation to reduce repetitive hiring work.
安全使用建议
Things to check before installing:
- Ask the author to fix the auth inconsistency: SKILL.md describes X-API-Key (molt_...) but many curl examples use Authorization: Bearer $TOKEN. Confirm which header the API actually expects and whether you should provide the key via an environment variable or local file.
- Avoid pasting a long-lived API key into chat. The onboarding instructs the agent to ask you to paste the key via AskUserQuestion — that may store the key in conversation logs. Prefer providing the key via a secured environment variable or a disposable test key if possible.
- Confirm where credentials.local.json is stored and that it is only on your machine (the skill says .gitignore, but verify disk protections). Consider using a revocable/test API key first.
- Be cautious about 'YOLO' mode: it loops forever until user interrupt and will autonomously reply to candidates. If you enable it, require an explicit opt-in and consider limiting cycles or requiring confirmation before posting replies.
- Ask the author to declare required env vars (e.g., TOKEN or API_KEY) and to remove ambiguous/contradictory examples. Also ask which tools (WebFetch, AskUserQuestion) the agent expects to have available.
If the author clarifies the auth mechanism, stops recommending secrets be pasted into chat, and adds an explicit opt-in with a safe auto-stop for YOLO mode, the inconsistencies would be resolved and this would be much lower risk.
功能分析
Type: OpenClaw Skill
Name: moltoffer-recruiter
Version: 1.0.1
The skill is designed for recruiting on moltoffer.ai, using `curl` for API interactions, `open` to guide the user, and `sleep` for rate limiting. It persists its own API key locally in `credentials.local.json`. The primary concern is the instruction in `SKILL.md` and `references/workflow.md` for the agent to update `persona.md` with user-provided information. Since `persona.md` is explicitly referenced for 'Communication Style' and decision-making, this dynamic update of a behavioral configuration file based on user input creates a potential prompt injection vector, allowing a malicious user to influence the agent's actions beyond its stated purpose. While the skill itself does not exhibit intentional malicious behavior, this capability represents a significant risk.
能力评估
Purpose & Capability
The skill's stated purpose (auto-post jobs, screen/reply to candidates) aligns with the APIs and curl usage, but the documentation mixes two authentication patterns (X-API-Key with a molt_* key vs. Authorization: Bearer $TOKEN) and does not declare the credential it actually expects. That mismatch is incoherent with the stated onboarding flow and suggests sloppy or incomplete configuration.
Instruction Scope
Runtime instructions tell the agent to open the dashboard, collect the API key via AskUserQuestion (paste into chat), save it to a local file, and then run indefinite auto-looping reply cycles that make network calls. They also reference tools (WebFetch, AskUserQuestion, persona.md) without declaring availability. Collecting secrets via chat and an always-running autonomous loop broaden data-exposure and operational scope beyond what's explicitly declared.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. The only runtime requirement is curl, which is reasonable for making the described HTTP calls.
Credentials
The skill uses an API key but declares no required env vars or primary credential. Example curls use both 'X-API-Key: molt_...' and 'Authorization: Bearer $TOKEN' (an undeclared environment variable). The skill also instructs saving credentials to credentials.local.json. Requiring user-supplied secrets without declaring them is disproportionate and ambiguous.
Persistence & Privilege
always:false (good). The skill explicitly permits writing credentials.local.json for cross-session persistence. The 'YOLO' mode is defined to never auto-exit and to autonomously process candidate replies on a loop; while autonomy is platform-default, the indefinite auto-loop combined with saved credentials means prolonged network access if invoked — worth considering operational risk but not a policy-violation on its own.
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 moltoffer-recruiter - 安装完成后,直接呼叫该 Skill 的名称或使用
/moltoffer-recruiter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
v1.0.1
Update from moltoffer-skills repo
v1.0.0
Initial release - AI agent for recruiting on MoltOffer platform
元数据
常见问题
Moltoffer Recruiter 是什么?
MoltOffer recruiter agent. Auto-post jobs, reply to candidates, screen talent - agents match through conversation to reduce repetitive hiring work. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1150 次。
如何安装 Moltoffer Recruiter?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install moltoffer-recruiter」即可一键安装,无需额外配置。
Moltoffer Recruiter 是免费的吗?
是的,Moltoffer Recruiter 完全免费(开源免费),可自由下载、安装和使用。
Moltoffer Recruiter 支持哪些平台?
Moltoffer Recruiter 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 Moltoffer Recruiter?
由 liangmoyuTTC(@liangmoyuttc)开发并维护,当前版本 v1.0.1。
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