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帮招聘 HR 快速汇总面试反馈、生成候选人推进话术、整理 Offer 材料并回写跟进记录。 / Help recruiting teams debrief interviews, draft candidate follow-ups, prepare offer materials, and update trackers.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/halojerry/poundingcore --skill cn-recruiting-workflowコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
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TL;DR: 23 marketing playbooks (CRO, SEO, copy, analytics, experiments, pricing, launches, ads, social). Use to get checklists + copy/paste deliverables fast.
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SOC 職業分類に基づく
SKILL.md を表示中
| name | cn-recruiting-workflow |
| description | 帮招聘 HR 快速汇总面试反馈、生成候选人推进话术、整理 Offer 材料并回写跟进记录。 / Help recruiting teams debrief interviews, draft candidate follow-ups, prepare offer materials, and update trackers. |
| version | 0.3.0 |
| metadata | {"openclaw":{"homepage":"https://github.com/Ashley-AIHR/hrskill","envVars":[{"name":"ATS_EXPORT_PATH","required":false,"description":"Optional local export path for tracker rows or CSV write-back."}]}} |
当用户在处理招聘推进、面试反馈汇总、候选人沟通或 Offer 前置材料时使用这个 skill。它更像一个会帮 HR 往前推流程的小助手，而不是一个只会解释概念的 HR 机器人。 / Use this skill when the user needs help moving recruiting work forward: interview debriefs, candidate follow-ups, and offer prep.
这个 skill 设计了 5 个招聘动作，目前已经有 2 个能真正落地交付文件的场景： / This skill is optimized for 5 recruiting actions, and currently has 2 production-ready scenarios:
互联网招聘里的面试反馈汇总与推进JD + 简历初筛与推进建议这个场景覆盖了互联网招聘里最常见的一类 HR 痛点： / That scenario covers a very common recruiting pain point:
当前附带了可直接使用的文件： / This skill includes bundled files for these scenarios:
支持的动作有： / The supported actions are:
score_candidatesummarize_interview_feedbackcreate_offer_approval_packgenerate_candidate_messageupdate_candidate_tracker处理任意招聘工作流时，始终产出以下结构： / When handling any recruiting workflow, always produce these sections:
normalized_data
decision_summary
missing_information
next_action
message_draft
record_update
compliance_warning_if_any
规则： / Rules:
normalized_data must be structured and easy to map into ATS, Feishu Bitable, DingTalk approval forms, Notion, Google Sheets, or CSV.decision_summary must make a decision or recommendation, not just restate the inputs.missing_information must name the exact fields that block a confident HR action.next_action must be something an HR operator can actually do today.message_draft should be directly reusable in WeCom, Feishu, email, or a candidate chat.record_update should be concise enough to write back into one row or one timeline entry.compliance_warning_if_any should only appear when there is a concrete legal or privacy concern.score_candidate当输入包含 JD 和简历或候选人资料时使用。 / Use when the input includes a JD and a resume or candidate profile.
常见输入形态： / Expected input shapes:
conservative, aggressive, fast-hiring, or high-bar至少抽取以下字段： / Always extract at least:
candidate_name
target_role
match_score
must_have_match
preferred_match
risk_flags
interview_focus
next_action
message_to_candidate
record_summary
summarize_interview_feedback当输入包含多位面试官意见、零散备注、聊天记录或表单片段时使用。 / Use when the input includes multiple interviewer comments, messy notes, chat transcripts, or form snippets.
这是当前版本里最完整的工作流。如果用户只要一个真正能从输入跑到产出的场景，优先使用它。 / This is the most complete workflow in the current version. If the user wants one concrete workflow that really works end-to-end, prefer this one.
将反馈归一化为： / Normalize feedback into:
interviewer_name
interview_round
capability_feedback
experience_feedback
motivation_feedback
communication_feedback
culture_fit_feedback
salary_risk
stability_risk
hire_recommendation
follow_up_questions
confidence_level
然后产出： / Then produce:
candidate_summary
interviewer_opinions
key_strengths
key_concerns
conflict_between_feedback
recommended_decision
follow_up_questions
candidate_reply_draft
record_summary
如果用户需要可下载文件，还要生成： / If the user wants downloadable artifacts, also generate:
如果在这个 skill 仓库本地运行，使用： / If working locally in this skill repo, use:
node scripts/generate_interview_packet.js <input.json> <output-dir>
示例输入见 assets/interview-packet-input.sample.json。 / See the sample payload in assets/interview-packet-input.sample.json.
score_candidate 也已支持文件产出如果用户希望把初筛结论直接落成文件，可以生成：
本地运行命令：
node scripts/generate_screening_packet.js <input.json> <output-dir>
create_offer_approval_pack当 HR 已经掌握足够候选人信息、准备发 Offer 前的内部审批材料时使用。 / Use when HR has enough candidate context to prepare an internal approval pack before sending an offer.
重点检查以下缺失或风险字段： / Check for missing or risky fields such as:
始终产出： / Always produce:
offer_approval_summary
candidate_value_summary
salary_budget_check
missing_fields
approval_recommendation
risk_notes
offer_message_draft
record_summary
generate_candidate_message当用户已经知道下一步动作，只需要一段面向候选人的沟通话术时使用。 / Use when the user already knows the intended next step and needs a candidate-facing message.
默认语气： / Default tone:
支持的意图： / Supported intents:
update_candidate_tracker当用户需要把结果回写到 ATS 或表格时使用。 / Use when the user wants a write-back summary for ATS or a spreadsheet.
默认 tracker 行格式： / Default tracker row format:
candidate_name
target_role
stage
decision
risk_flags
owner
next_action
last_update_summary
如果用户提供已有 tracker schema，则优先遵循用户 schema。 / If the user provides an existing tracker schema, follow that schema instead.
Keep outputs aligned with common recruiting practice in China:
For common field shapes and examples, see references/recruiting-fields.md. For the detailed production-ready workflow, see references/real-user-scenario.md.