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做定薪判断，也先把申报前风险挑出来 / Price offers and catch filing risks\n\nTags: china:0.2.0, compensation:0.2.0, hr:0.2.0, latest:0.5.0, payroll:0.2.0\n\nVersion history:\n\nv0.5.0 | 2026-05-18T20:34:48.346Z | auto\n\n**Summary:** \nIntroduces dynamic market data handling, clearer output protocols, and improved decision logic for compensation and payroll checks.\n\n- Added support for dynamic market data input and output with new sample assets.\n- Refined workflow routing based on input content; now distinguishes between official, market, survey, and internal data sources.\n- Updated output structure to require explicit decision summaries, bases, risk levels, and human confirmation steps.\n- Improved clarity of documentation and protocols, including updated SKILL.md with new requirements and principles.\n- Expanded references and sample scenarios, including latest China compensation policy and market data architecture guides.\n\nv0.2.0 | 2026-05-18T19:59:04.871Z | user\n\nAdd a second production-ready scenario for compensation band review, market benchmark summary, and offer pricing recommendation, alongside payroll filing prechecks.\n\nv0.1.0 | 2026-05-18T19:56:11.372Z | user\n\nInitial release: a China-focused payroll filing precheck skill for IIT, social insurance, and housing fund submission risk checks.\n\nArchive index:\n\nArchive v0.5.0: 19 files, 30208 bytes\n\nFiles: agents/openai.yaml (418b), assets/band-offer-review-input.dynamic.sample.json (2189b), assets/band-offer-review-input.sample.json (1509b), assets/generated-band-dynamic-sample/band-offer-review-output.json (3285b), assets/generated-band-dynamic-sample/band-offer-review.csv (299b), assets/generated-band-sample/band-offer-review-output.json (2563b), assets/generated-band-sample/band-offer-review.csv (296b), assets/generated-sample/payroll-filing-precheck-output.json (4697b), assets/generated-sample/payroll-filing-precheck.csv (978b), assets/payroll-precheck-input.sample.json (2814b), references/china-compensation-policy-kb-2026.md (8362b), references/compensation-workflows.md (1092b), references/dynamic-market-data-architecture.md (3480b), references/real-user-scenario.md (3159b), scripts/generate_band_offer_packet.js (10605b), scripts/generate_payroll_precheck_packet.js (9194b), skill-card.md (3272b), SKILL.md (5887b), _meta.json (141b)\n\nFile v0.5.0:SKILL.md\n\n---\nname: hr-compensation-checks\ndescription: 帮 HR 做定薪判断、band 对标、市场调研摘要，以及个税社保公积金申报前检查，先看值不值，再看会不会出风险。 / Help HR teams with compensation review, band and market checks, and payroll filing prechecks.\nversion: 0.5.0\nmetadata:\n openclaw:\n homepage: https://github.com/Ashley-AIHR/hrskill-compensation-module\n envVars:\n - name: COMP_EXPORT_PATH\n required: false\n description: Optional local export path for filing check outputs.\n---\n\n# 定薪与申报检查助手 / Compensation Decision Assistant\n\n当用户在处理两类薪酬工作时使用这个 skill：\n\n1. 定薪判断：band、市场调研、内部公平、offer 建议\n2. 申报检查：个税、社保、公积金申报前排雷\n\n目标不是手算工资，而是输出：\n\n1. 结论\n2. 依据\n3. 风险\n4. 待办\n5. 可直接发给内部协作方的说明\n\n如果用户第一次使用或输入很乱，先读 [references/real-user-scenario.md](references/real-user-scenario.md)。\n如果需要工作流背景，读 [references/compensation-workflows.md](references/compensation-workflows.md)。\n如果需要最新政策、城市口径和系统操作依据，读 [references/china-compensation-policy-kb-2026.md](references/china-compensation-policy-kb-2026.md)。\n如果需要理解动态市场数据怎么分层、哪些能当正式依据，读 [references/dynamic-market-data-architecture.md](references/dynamic-market-data-architecture.md)。\n\n## 路由规则\n\n根据输入内容路由到下面动作之一：\n\n1. `review_compensation_band_and_offer`\n 触发条件：输入里有 band、市场分位、候选人期望、内部参考、预算中的任意组合。\n2. `precheck_payroll_filing`\n 触发条件：输入里有个税、社保、公积金申报字段，或月度申报名单、员工状态、主体信息。\n\n如果用户不知道该选哪个动作：\n\n1. 有申报名单、基数、主体、缴纳地，就走 `precheck_payroll_filing`\n2. 有 band、市场分位、候选人期望，就走 `review_compensation_band_and_offer`\n\n对 `review_compensation_band_and_offer`，必须区分：\n\n1. `official_policy`\n2. `public_market_signal`\n3. `paid_survey_data`\n4. `internal_company_data`\n\n如果只有 `public_market_signal`，不允许把结论写成正式定薪建议。\n\n## 输出协议\n\n处理任意薪酬场景时，始终输出：\n\n```text\nnormalized_data\ndecision_summary\ndecision_basis\nmissing_information\nrisk_summary\npriority_issues\nnext_action\nmessage_draft\nrecord_update\nhuman_confirmation_needed\ncompliance_warning_if_any\n```\n\n要求：\n\n1. `decision_summary` 必须先回答“怎么定”或“能不能报”。\n2. `decision_basis` 必须把 band、市场、内部参考或申报依据讲清楚。\n3. `missing_information` 只写真正影响判断或申报的缺口。\n4. `risk_summary` 优先写申报失败风险、内部公平风险、预算风险。\n5. `priority_issues` 必须按高、中、低排序。\n6. `next_action` 必须是 HR 今天能做的动作。\n7. `message_draft` 默认写给业务负责人、薪酬同事或数据提供方。\n8. `human_confirmation_needed` 必须写清楚还要谁确认什么。\n9. 对定薪场景，必须标明本次结论属于 `正式建议`、`弱建议` 还是 `仅市场信号判断`。\n\n## 动作要求\n\n### `review_compensation_band_and_offer`\n\n至少抽取：\n\n```text\njob_family\njob_level\nband_min\nband_mid\nband_max\nmarket_p25\nmarket_p50\nmarket_p75\ncandidate_current_pay\ncandidate_expected_pay\ninternal_peer_reference\nbudget_range\n```\n\n并优先识别：\n\n```text\nofficial_policy\npublic_market_signal\npaid_survey_data\ninternal_company_data\ncandidate_total_comp_context\n```\n\n结果优先顺序：\n\n1. 建议怎么定\n2. 为什么这么定\n3. 内部公平或预算风险\n4. 怎么和业务解释\n5. 还需要谁确认\n\n判断规则：\n\n1. 同时具备 `internal_company_data + paid_survey_data + candidate_current_pay_or_total_comp + budget_range` 时，才可给 `正式建议`\n2. 只有 `public_market_signal` 时，只能给 `市场信号判断`\n3. 缺少 `band` 或 `internal_company_data` 时，不得假装能完成内部公平判断\n4. 缺少 `budget_range` 时，不得假装能完成审批级建议\n5. 缺少 `candidate_current_pay` 或总包口径时，要主动降低结论强度\n\n如果需要文件产出，运行：\n\n```text\nnode scripts/generate_band_offer_packet.js \n```\n\n示例输入： [assets/band-offer-review-input.sample.json](assets/band-offer-review-input.sample.json)\n动态分层示例输入： [assets/band-offer-review-input.dynamic.sample.json](assets/band-offer-review-input.dynamic.sample.json)\n\n### `precheck_payroll_filing`\n\n至少抽取：\n\n```text\nemployee_name\nemployee_status\nlegal_entity\nwork_city\nfiling_city\nbank_account_status\nid_number_status\ntaxable_income\nsocial_base\nhousing_fund_base\nspecial_deduction_status\n```\n\n结果优先顺序：\n\n1. 能不能直接报\n2. 高风险问题\n3. 按人列出的缺口\n4. 今天先处理什么\n5. 给内部同事的追回或提醒话术\n\n如果需要文件产出，运行：\n\n```text\nnode scripts/generate_payroll_precheck_packet.js \n```\n\n示例输入： [assets/payroll-precheck-input.sample.json](assets/payroll-precheck-input.sample.json)\n\n## 工作原则\n\n1. 先给结论，再给依据，再给待办。\n2. 输入默认不干净，先归一化，不要要求用户先自己整理完。\n3. 申报检查优先抓“漏人、错主体、错城市、错基数、缺字段”。\n4. 定薪判断优先看 band、市场和内部公平，不要只盯一个数字。\n5. 缺政策口径或核心字段时，不要装得很确定，要明确降置信度。\n6. 不自动给法律结论，但要明确提示合规风险。\n7. 对公网职位薪资，只能当作市场信号，不能冒充正式薪酬调研。\n\nFile v0.5.0:_meta.json\n\n{\n \"ownerId\": \"kn7cfgqtq1167ctj7rfp8cg3yn840js9\",\n \"slug\": \"hr-compensation-checks\",\n \"version\": \"0.5.0\",\n \"publishedAt\": 1779136488346\n}\n\nFile v0.5.0:references/china-compensation-policy-kb-2026.md\n\n# 中国薪酬申报与定薪知识库\n\n更新时间：2026-05-19\n\n这份文件只收录两类内容：\n\n1. 会随着时间、城市、系统流程变化的动态资料\n2. 可以直接支撑薪酬 skill 判断的政策与操作依据\n\n它不是完整政策汇编，而是给 skill 用的最小知识库。\n\n## 先给结论\n\n截至 2026-05-19，当前 repo 里原本并没有真正把这些动态资料接进去。\n\n最明显的缺口有 4 个：\n\n1. 没有按城市维护社保、公积金口径\n2. 没有按年度维护社保缴费工资申报周期\n3. 没有把个税扣缴端和 WEB 端的真实操作限制接进去\n4. 没有把“哪些数据能公开动态获取、哪些不能”说清楚\n\n所以如果这个 skill 要从 prototype 变成 professional-grade，至少要从这份知识库起步。\n\n## 一、社保年度缴费工资申报：这是真正会变的动态资料\n\n### 上海：2026 社保年度申报已经变化\n\n官方来源：\n\n1. 国家税务总局上海市税务局\n [关于开展2026社保年度用人单位社会保险缴费工资申报工作的通告](https://shanghai.chinatax.gov.cn/zcfw/zcfgk/sbf/202604/t480144.html)\n2. 国家税务总局上海市税务局\n [一图了解：上海市2026社保年度用人单位社会保险缴费工资申报](https://shanghai.chinatax.gov.cn/zcfw/tjss/202605/t480288.html)\n\n截至 2026-05-19，关键动态口径是：\n\n1. 申报时间：2026-05-01 至 2026-06-25\n2. 对应社保年度：2026-07 至 2027-06\n3. 用人单位要按 2025-01-01 至 2025-12-31 的上一自然年度月平均工资申报\n4. 上一年工作不满一年的职工，按工资总额除以实际工作月数计算\n5. 2026 年新招录职工，以起薪当月全月工资收入申报\n6. 申报渠道至少包括上海电子税务局、社保费管理客户端、办税服务厅\n\n这意味着：\n\n1. `precheck_payroll_filing` 不能只做“当月申报前检查”\n2. 还必须知道当前是不是处在“年度缴费工资申报窗口”\n3. 对上海场景，必须区分“月度申报前检查”和“年度基数申报检查”\n\n## 二、公积金：北京、深圳都不是静态规则\n\n### 北京：社保工资与公积金基数已经开始联动\n\n官方来源：\n\n1. 北京住房公积金管理中心\n [2025住房公积金年度缴存基数申报常见问题解答](https://gjj.beijing.gov.cn/web/zwfw5/1747335/1747336/743669918/index.html)\n2. 北京住房公积金管理中心\n [《关于2025住房公积金年度缴存有关问题的通知》政策解读](https://gjj.beijing.gov.cn/web/zwgk61/2024zcjd/743765478/index.html)\n3. 北京住房公积金管理中心\n [《关于用人单位和灵活就业人员申报2025年度社会保险费缴费工资（缴费基数）有关事项的通告》（住房公积金部分）政策解读](https://gjj.beijing.gov.cn/web/zwgk61/2024zcjd/743660449/)\n\n截至 2026-05-19，关键口径是：\n\n1. 2025 公积金年度为 2025-07-01 至 2026-06-30\n2. 缴存比例仍是 5% 至 12%\n3. 月缴存基数上限为 35811 元\n4. 自 2025-09-01 起，月缴存基数下限为 2540 元\n5. 领取基本生活费职工的下限为 1778 元\n6. 单位可授权公积金中心获取已向税务部门申报的社保缴费工资，作为核定公积金缴存基数的“上年月均工资”\n\n这意味着：\n\n1. 北京场景下，公积金不能完全当成一套独立口径\n2. skill 需要知道“社保年度申报数据是否已经可供授权获取”\n3. 如果企业是在 6 月到 7 月切换窗口期，系统要提醒“缴存基数申报”和“7 月汇缴名单确认”的顺序风险\n\n### 深圳：2026 年公积金规则也在变\n\n官方来源：\n\n1. 深圳政府在线\n [深圳新版住房公积金管理办法下月起施行](https://www.sz.gov.cn/cn/xxgk/zfxxgj/zwdt/content/post_12687780.html)\n2. 深圳市住房和建设局\n [缴存基数调整有什么要求？](https://zjj.sz.gov.cn/zcjzts/content/post_12322480.html)\n3. 深圳市住房公积金管理中心问答\n [个人缴存比例从2026年4月1日起就能申请调整，还是要等到7月1日才能调整？](https://zjj.sz.gov.cn/szszfhjsjwzgkml/szszfhjsjwzgkml/seztfw/zfly/wyw/ywzsk/content/post_12703688.html)\n\n截至 2026-05-19，关键口径是：\n\n1. 深圳新版《住房公积金管理办法》在 2026-04 起进入新阶段\n2. 每个住房公积金年度为当年 7 月 1 日至次年 6 月 30 日\n3. 职工可在单位缴存比例基础上，自愿申请提高个人缴存比例\n4. 调整后的个人缴存比例最高不超过 12%\n5. 在每个住房公积金年度内，职工可调整一次个人缴存比例\n\n这意味着：\n\n1. 深圳场景不只要检查缴存基数，还要检查“个人缴存比例是否已在年度内调整过”\n2. 如果把深圳用户当成和北京、上海完全同一套逻辑，会误判\n\n## 三、个税扣缴：真实工作不是“算税”，而是“系统约束 + 数据恢复 + 更正逻辑”\n\n官方来源：\n\n1. 国家税务总局上海市税务局\n [自然人扣缴端热点操作问答](https://shanghai.chinatax.gov.cn/jstax/ztzl/yshj/sycz/202512/t478537.html)\n2. 国家税务总局广东省税务局转发\n [自然人电子税务局WEB端扣缴业务等相关功能操作指南](https://guangdong.chinatax.gov.cn/gdsw/zqsw_tzgg/2020-11/18/content_75df0d6a19634d9596f0bffd81492a5c.shtml)\n\n截至 2026-05-19，对 skill 最有用的不是税率本身，而是这些操作型事实：\n\n1. 扣缴端数据丢失时，不是所有企业都能直接恢复\n2. 办税人员可能需要先申请开通“扣缴端数据下载”权限\n3. 上海税务口径下，开通后可在 72 小时内下载数据\n4. 分部门申报的企业，数据下载存在限制\n5. WEB 端和扣缴端都支持人员信息、专项附加扣除信息、扣缴申报、查询统计等模块\n\n这意味着：\n\n1. `precheck_payroll_filing` 不能只假设数据永远齐全\n2. 要把“系统数据恢复能力”和“历史申报数据可追溯性”纳入风险提示\n3. 对个税场景，skill 的下一步动作不能只写“去补数据”，还应写“是否能从扣缴端或 WEB 端回补历史数据”\n\n## 四、什么是公开动态可得的，什么不是\n\n这是薪酬 skill 最容易装懂的地方。\n\n### 可以公开动态获取的\n\n1. 社保年度缴费工资申报时间\n2. 电子税务局申报路径\n3. 公积金年度、缴存比例上下限、办理路径\n4. 部分扣缴端 / WEB 端操作规则\n5. 官方法规、解读、问答、公告\n\n### 不能依赖公网直接稳定获取的\n\n1. 企业自己的 band 表\n2. 企业内部同岗同级薪酬参考\n3. 企业年度调薪预算\n4. 权威、细颗粒度、可自动抓取的市场薪酬分位数据\n5. 企业历史 offer 决策记录\n\n所以：\n\n1. `review_compensation_band_and_offer` 不能假装“上网就能给出定薪结论”\n2. 它必须要求用户上传 band、内部参考、市场调研\n3. 否则最多只能给结构化问题清单，不能给真正的定薪建议\n\n## 五、这份知识库对 skill 设计的直接要求\n\n### 对 `precheck_payroll_filing`\n\n至少要新增这些判断层：\n\n1. `city_policy_context`\n2. `social_insurance_year_window`\n3. `housing_fund_year_window`\n4. `withholding_system_recovery_constraints`\n5. `entity_city_mismatch_risk`\n\n### 对 `review_compensation_band_and_offer`\n\n至少要新增这些判断前提：\n\n1. 是否有 band\n2. 是否有市场调研分位点\n3. 是否有内部同岗同级参考\n4. 是否有预算范围\n5. 是否有候选人当前薪资或总包口径\n\n如果没有这些前提，就不能装成“专业定薪判断”。\n\n## 六、当前 skill 的真实评价\n\n截至 2026-05-19：\n\n1. 现在 repo 里的薪酬 skill 还没有真正消费这份知识库\n2. 它目前更像结构原型，不是知识驱动型 skill\n3. 如果不把这类动态资料接入，所谓“专业判断”就是假的\n\n## 七、建议下一步落地方式\n\n最小可行改造不是“再写更多 prompt”，而是：\n\n1. 先做 `policy_profile` 文件\n 例如 `shanghai-2026-social-insurance.md`\n2. 再做 `city-rule-matrix.json` 或 Markdown 规则表\n3. 然后让 `precheck_payroll_filing` 先支持 1 到 2 个城市\n4. 对定薪判断，明确区分：\n - 官方动态资料\n - 企业上传数据\n - 无法外部获取的数据\n\n只有这样，这个薪酬 skill 才能从“看起来像懂”变成“真的有依据”。\n\nFile v0.5.0:references/compensation-workflows.md\n\n# 中国 HR 薪酬高频工作流\n\n这个 skill 当前只先做一个场景，但背后的工作流语境来自中国 HR 常见的薪酬操作链路。\n\n## 常见月度链路\n\n1. 人员异动确认\n2. 考勤、绩效、补发补扣等数据收集\n3. 算薪\n4. 差异复核\n5. 个税申报\n6. 社保申报\n7. 公积金汇缴\n8. 发薪与留痕\n\n## 当前最适合 AI 的两个切入点\n\n### 1. 薪酬判断\n\n包括：\n\n1. 薪酬 band 校验\n2. 市场调研摘要\n3. 定薪建议\n\n这类工作适合做“高阶判断型 Skill”，因为它很像资深 HR 脑子里的隐性判断。\n\n### 2. 申报前检查\n\n第一版不做完整算薪，而做：\n\n1. `band / 调研 / 定薪建议`\n2. `申报前检查`\n\n原因：\n\n1. 一个负责专业感与判断感\n2. 一个负责落地感与风险感\n3. 两者合在一起，才更像真实中国薪酬模块\n\n## 当前最应该优先识别的问题\n\n1. 人员漏报\n2. 离职人员仍在申报名单\n3. 申报主体错误\n4. 缴纳地错误\n5. 社保、公积金基数异常\n6. 专项附加扣除信息缺失或异常\n7. 银行卡或身份证号缺失\n\nFile v0.5.0:references/dynamic-market-data-architecture.md\n\n# 薪酬市场动态数据架构\n\n更新时间：2026-05-19\n\n这份文件回答 3 个问题：\n\n1. 薪酬市场调研数据从哪里来\n2. 哪些数据可以动态拿，哪些不能\n3. skill 应该如何区分“市场信号”和“正式定薪依据”\n\n## 一、核心原则\n\n薪酬 skill 不能把所有数据都当成同一种证据。\n\n至少要区分 4 层：\n\n1. `official_policy`\n 官方动态资料，例如国家统计局、税务局、公积金中心、地方人社口径\n2. `public_market_signal`\n 公网职位薪资、招聘平台公开区间、景气和招聘热度\n3. `paid_survey_data`\n 企业采购的薪酬调研结果，例如 Mercer、智联企业薪酬调研等\n4. `internal_company_data`\n 企业自己的 band、内部同岗参考、预算、历史 offer、接受率\n\n## 二、每一层能做什么\n\n### `official_policy`\n\n能支持：\n\n1. 合规边界\n2. 城市年度口径\n3. 社保、公积金、个税相关约束\n4. 宏观工资趋势\n\n不能直接支持：\n\n1. 某一岗位的精准定薪\n2. 某一级别的 P50/P75 报价\n\n### `public_market_signal`\n\n能支持：\n\n1. 当前市场招聘热度\n2. 公开薪资区间趋势\n3. 城市、行业、岗位的招聘侧价格信号\n\n不能直接支持：\n\n1. 最终成交薪资\n2. 企业内部公平\n3. 可审计的正式定薪依据\n\n所以它最多只能作为：\n\n`market signal only`\n\n### `paid_survey_data`\n\n能支持：\n\n1. 分城市、分岗位、分级别的市场分位点\n2. 定薪、调薪、band 校准\n3. 对业务或老板的正式解释材料\n\n这是最接近真实薪酬 benchmark 的外部数据。\n\n### `internal_company_data`\n\n能支持：\n\n1. band 判断\n2. 内部公平判断\n3. 预算约束\n4. 历史 offer 一致性\n5. 真正的审批建议\n\n这是最终定薪最关键的一层。\n\n## 三、skill 的判断权重\n\n对于 `review_compensation_band_and_offer`，建议使用下面的判断优先级：\n\n1. `internal_company_data`\n2. `paid_survey_data`\n3. `public_market_signal`\n4. `official_policy`\n\n## 四、什么时候允许 skill 给出强结论\n\n### 可以给“正式建议”\n\n至少满足：\n\n1. 有 `band`\n2. 有 `internal_company_data`\n3. 有 `paid_survey_data` 或高质量市场分位点\n4. 有候选人当前薪资或总包口径\n5. 有预算范围\n\n### 只能给“弱建议”或“仅市场信号判断”\n\n如果出现这些情况：\n\n1. 只有公网职位薪资，没有正式调研\n2. 没有内部 band\n3. 没有内部同岗同级参考\n4. 没有预算\n5. 候选人只有期望薪资，没有当前薪资或总包口径\n\n这时 skill 必须主动说：\n\n1. 当前只能给市场信号判断\n2. 不能作为正式定薪依据\n3. 还缺哪些数据\n\n## 五、建议的输入结构\n\n建议每次定薪判断输入都显式区分来源：\n\n```text\npolicy_context\npublic_market_signal\npaid_survey_data\ninternal_company_data\ncandidate_compensation_context\n```\n\n不要把所有东西都混在一个 `market_benchmark` 里。\n\n## 六、最小可行动态方案\n\n如果现在就要做一个“动态版薪酬 skill”，最实际的路线是：\n\n1. 官方动态口径：由 skill 内置并定期更新\n2. 公网市场信号：允许用户补充或人工抓取摘要\n3. 正式调研数据：由用户上传最新报告或 Excel\n4. 企业内部数据：由用户上传 band、预算、内部参考\n\n也就是说：\n\n`动态` 不等于 `全靠 skill 自己上网抓`\n\n而是：\n\n`skill 能持续消费会变化的数据，并且知道每种数据能撑起多强的判断`\n\nFile v0.5.0:references/real-user-scenario.md\n\n# 定薪与申报检查助手：真实用户场景\n\n## 这个 skill 最适合从哪里开始\n\n第一次打开时，优先从这两个场景开始：\n\n1. `做申报前检查`\n2. `做定薪判断`\n\n它们分别承担两种完全不同但都很真实的使用心智：\n\n1. `做申报前检查`\n 这是“月底快报了，先帮我排雷”\n2. `做定薪判断`\n 这是“这个价到底能不能给，怎么解释更稳”\n\n## 推荐第一生产场景\n\n`月末准备做个税、社保、公积金申报，HR 想先做一轮检查`\n\n这非常真实，因为：\n\n1. 月度薪酬数据总会有缺口\n2. 申报前最后一轮检查非常耗 HR 时间\n3. 真正让 HR 紧张的不是“填表”，而是“怕申报失败或错报”\n\n### 用户第一次可以这样说\n\n1. `这是本月申报名单，帮我看看有没有高风险问题。`\n2. `个税、社保、公积金申报前先帮我排一下雷。`\n3. `哪些人缺字段，哪些人基数或主体有问题，给我一个待办清单。`\n\n### 用户至少要给什么\n\n1. 本月薪酬或申报名单\n2. 个税申报字段\n3. 社保、公积金申报字段\n4. 员工状态、法人主体和缴纳地信息\n\n### 用户最希望拿到什么\n\n1. 能不能直接报\n2. 哪些人最危险\n3. 缺了什么字段\n4. 今天先追回什么\n5. 给内部同事的提醒话术\n\n### 结果页要优先按这个顺序展示\n\n1. `能不能直接报`\n2. `高风险问题`\n3. `按人列出的缺口`\n4. `今天先处理什么`\n5. `内部提醒或追回话术`\n\n## 推荐第二生产场景\n\n`准备发 offer 或做关键岗位定薪，HR 想先看 band、市场和内部公平`\n\n这也非常真实，因为：\n\n1. 薪酬判断并不是拍脑袋\n2. 定薪最难的是把市场、band、候选人期望和内部公平放在一起看\n3. 这也是最适合做“专业感 + 传播感”的薪酬场景\n\n### 用户第一次可以这样说\n\n1. `这个候选人期望 40k，到底能不能给？`\n2. `帮我看看这个 offer 是在 band 里什么位置。`\n3. `把市场分位、内部参考和定薪建议整理成一版摘要。`\n\n### 用户至少要给什么\n\n1. 岗位级别和 band\n2. 市场调研分位点\n3. 候选人当前或期望薪资\n4. 内部同岗同级参考\n5. 可选的预算或审批口径\n\n### 用户最希望拿到什么\n\n1. 建议怎么定\n2. 为什么这么定\n3. 有没有内部公平风险\n4. 怎么和业务解释\n5. 还需要谁确认\n\n## 这个 skill 背后的真实薪酬语境\n\n它要默认理解这些情况：\n\n1. 申报前数据往往来自多个表，不会天然干净\n2. band、市场和内部公平经常是分开存放的\n3. 薪酬负责人最怕的不是“慢一点”，而是“错报”和“解释不清”\n\n## 哪些地方不要装得太确定\n\n如果出现这些情况，要主动收窄判断：\n\n1. 城市口径未提供\n2. 只有期望薪资，没有当前薪资或总包口径\n3. band 规则缺少中位值、级差或预算信息\n4. 个税、社保、公积金数据口径彼此不一致\n5. 员工状态或法人主体信息不完整\n\n此时要明确写出：\n\n1. `当前判断依据不足`\n2. `哪些结论只是初筛`\n3. `还需要谁确认`\n4. `建议先补什么数据`\n\nFile v0.5.0:skill-card.md\n\n## Description:\n\nHelps HR teams review compensation bands, market signals, offer decisions, and payroll filing prechecks.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[ashley-aihr](https://clawhub.ai/user/ashley-aihr)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nHR and compensation teams use this skill to decide whether an offer fits company bands, market data, internal fairness, and budget constraints, or whether a payroll filing packet has employee, entity, city, tax, social insurance, or housing fund risks that need follow-up.\n\n### Deployment Geography for Use:\n\nChina\n\n## Known Risks and Mitigations:\n\nRisk: Sensitive payroll and compensation data may be written into local plaintext report files.\n\nMitigation: Use the skill only in a controlled HR environment, choose a private output directory, avoid shared drives, and retain or delete generated files according to employee-data policy.\n\nRisk: Generated CSV files may be unsafe to open in spreadsheet software when inputs come from untrusted sources.\n\nMitigation: Review generated files before forwarding or opening them in spreadsheet tools, especially when any input data was supplied by an untrusted party.\n\nRisk: Compensation recommendations can be misleading when band, market, internal peer, budget, or candidate compensation inputs are incomplete.\n\nMitigation: Require human confirmation for missing or low-confidence inputs and treat public market signals as non-authoritative unless supported by paid survey data and internal company data.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/ashley-aihr/skills/hr-compensation-checks)\n- [Project homepage](https://github.com/Ashley-AIHR/hrskill-compensation-module)\n- [China compensation policy knowledge base](references/china-compensation-policy-kb-2026.md)\n- [China HR compensation workflows](references/compensation-workflows.md)\n- [Dynamic market data architecture](references/dynamic-market-data-architecture.md)\n- [Real user scenario](references/real-user-scenario.md)\n- [Shanghai 2026 social insurance wage declaration notice](https://shanghai.chinatax.gov.cn/zcfw/zcfgk/sbf/202604/t480144.html)\n- [Beijing housing fund annual base FAQ](https://gjj.beijing.gov.cn/web/zwfw5/1747335/1747336/743669918/index.html)\n- [Shenzhen housing fund rule update](https://www.sz.gov.cn/cn/xxgk/zfxxgj/zwdt/content/post_12687780.html)\n- [Shanghai withholding client operation FAQ](https://shanghai.chinatax.gov.cn/jstax/ztzl/yshj/sycz/202512/t478537.html)\n\n## Skill Output:\n\n**Output Type(s):** [Guidance, Markdown, JSON, Code, Shell commands, Configuration]\n\n**Output Format:** [Markdown guidance with structured fields; optional generated JSON, CSV, and DOCX report files from bundled scripts]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May write local compensation or payroll report files when the user runs the packet-generation scripts.]\n\n## Skill Version(s):\n\n0.5.0 (source: frontmatter and server release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v0.5.0:assets/band-offer-review-input.dynamic.sample.json\n\n{\n \"meta\": {\n \"workflow\": \"review_compensation_band_and_offer\",\n \"prepared_by\": \"HRBP\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"decision_mode\": \"formal_pricing_review\"\n },\n \"position\": {\n \"job_title\": \"高级用户增长产品经理\",\n \"job_family\": \"产品\",\n \"level\": \"P7\",\n \"city\": \"上海\"\n },\n \"policy_context\": {\n \"city\": \"上海\",\n \"policy_year\": \"2026\",\n \"notes\": \"用于提供城市与合规背景，不直接作为岗位定薪分位点。\"\n },\n \"public_market_signal\": {\n \"enabled\": true,\n \"source_summary\": \"公开招聘平台近30天同城增长产品岗位薪资区间观察\",\n \"range_min\": 35000,\n \"range_max\": 48000,\n \"confidence\": \"low\",\n \"notes\": \"仅作为公开招聘市场信号，不作为正式定薪依据。\"\n },\n \"paid_survey_data\": {\n \"source_name\": \"企业采购薪酬调研\",\n \"sample_scope\": \"上海 互联网 / 产品增长 / P7\",\n \"p25\": 34000,\n \"p50\": 39000,\n \"p75\": 46000,\n \"effective_date\": \"2026-04-30\",\n \"confidence\": \"high\",\n \"notes\": \"近12个月互联网增长产品岗位样本。\"\n },\n \"internal_company_data\": {\n \"band\": {\n \"currency\": \"CNY\",\n \"monthly_base_min\": 32000,\n \"monthly_base_mid\": 38000,\n \"monthly_base_max\": 45000\n },\n \"budget_range\": {\n \"min\": 36000,\n \"max\": 43000\n },\n \"same_level_employees\": [\n {\n \"employee_name\": \"A\",\n \"monthly_base\": 36500,\n \"note\": \"P7，增长产品，司龄2年\"\n },\n {\n \"employee_name\": \"B\",\n \"monthly_base\": 38800,\n \"note\": \"P7，用户增长，司龄1年\"\n },\n {\n \"employee_name\": \"C\",\n \"monthly_base\": 41000,\n \"note\": \"P7，核心增长岗，历史调薪后\"\n }\n ]\n },\n \"candidate_compensation_context\": {\n \"candidate_name\": \"周子涵\",\n \"current_title\": \"增长产品负责人\",\n \"current_company\": \"某内容平台\",\n \"current_monthly_base\": 36000,\n \"expected_monthly_base\": 42000,\n \"target_role_reason\": \"有会员增长、增长实验和跨团队主导经验，业务方反馈较强，属于重点候选人。\"\n }\n}\n\nFile v0.5.0:assets/band-offer-review-input.sample.json\n\n{\n \"meta\": {\n \"workflow\": \"review_compensation_band_and_offer\",\n \"prepared_by\": \"HRBP\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\"\n },\n \"position\": {\n \"job_title\": \"高级用户增长产品经理\",\n \"job_family\": \"产品\",\n \"level\": \"P7\",\n \"city\": \"上海\"\n },\n \"band\": {\n \"currency\": \"CNY\",\n \"monthly_base_min\": 32000,\n \"monthly_base_mid\": 38000,\n \"monthly_base_max\": 45000\n },\n \"market_benchmark\": {\n \"sample_scope\": \"上海 互联网 / 产品增长 / P7\",\n \"p25\": 34000,\n \"p50\": 39000,\n \"p75\": 46000,\n \"notes\": \"市场样本以近 12 个月互联网增长产品岗位为主，头部平台给价更高。\"\n },\n \"candidate\": {\n \"candidate_name\": \"周子涵\",\n \"current_title\": \"增长产品负责人\",\n \"current_company\": \"某内容平台\",\n \"current_monthly_base\": 36000,\n \"expected_monthly_base\": 42000,\n \"target_role_reason\": \"有会员增长、增长实验和跨团队主导经验，业务方反馈较强，属于重点候选人。\"\n },\n \"internal_reference\": {\n \"same_level_employees\": [\n {\n \"employee_name\": \"A\",\n \"monthly_base\": 36500,\n \"note\": \"P7，增长产品，司龄 2 年\"\n },\n {\n \"employee_name\": \"B\",\n \"monthly_base\": 38800,\n \"note\": \"P7，用户增长，司龄 1 年\"\n },\n {\n \"employee_name\": \"C\",\n \"monthly_base\": 41000,\n \"note\": \"P7，核心增长岗，历史调薪后\"\n }\n ]\n }\n}\n\nFile v0.5.0:assets/generated-band-dynamic-sample/band-offer-review-output.json\n\n{\n \"normalized_data\": {\n \"meta\": {\n \"workflow\": \"review_compensation_band_and_offer\",\n \"prepared_by\": \"HRBP\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"decision_mode\": \"formal_pricing_review\"\n },\n \"position\": {\n \"job_title\": \"高级用户增长产品经理\",\n \"job_family\": \"产品\",\n \"level\": \"P7\",\n \"city\": \"上海\"\n },\n \"policy_context\": {\n \"city\": \"上海\",\n \"policy_year\": \"2026\",\n \"notes\": \"用于提供城市与合规背景，不直接作为岗位定薪分位点。\"\n },\n \"public_market_signal\": {\n \"enabled\": true,\n \"source_summary\": \"公开招聘平台近30天同城增长产品岗位薪资区间观察\",\n \"range_min\": 35000,\n \"range_max\": 48000,\n \"confidence\": \"low\",\n \"notes\": \"仅作为公开招聘市场信号，不作为正式定薪依据。\"\n },\n \"paid_survey_data\": {\n \"source_name\": \"企业采购薪酬调研\",\n \"sample_scope\": \"上海 互联网 / 产品增长 / P7\",\n \"p25\": 34000,\n \"p50\": 39000,\n \"p75\": 46000,\n \"effective_date\": \"2026-04-30\",\n \"confidence\": \"high\",\n \"notes\": \"近12个月互联网增长产品岗位样本。\"\n },\n \"internal_company_data\": {\n \"band\": {\n \"currency\": \"CNY\",\n \"monthly_base_min\": 32000,\n \"monthly_base_mid\": 38000,\n \"monthly_base_max\": 45000\n },\n \"budget_range\": {\n \"min\": 36000,\n \"max\": 43000\n },\n \"same_level_employees\": [\n {\n \"employee_name\": \"A\",\n \"monthly_base\": 36500,\n \"note\": \"P7，增长产品，司龄2年\"\n },\n {\n \"employee_name\": \"B\",\n \"monthly_base\": 38800,\n \"note\": \"P7，用户增长，司龄1年\"\n },\n {\n \"employee_name\": \"C\",\n \"monthly_base\": 41000,\n \"note\": \"P7，核心增长岗，历史调薪后\"\n }\n ]\n },\n \"candidate_compensation_context\": {\n \"candidate_name\": \"周子涵\",\n \"current_title\": \"增长产品负责人\",\n \"current_company\": \"某内容平台\",\n \"current_monthly_base\": 36000,\n \"expected_monthly_base\": 42000,\n \"target_role_reason\": \"有会员增长、增长实验和跨团队主导经验，业务方反馈较强，属于重点候选人。\"\n }\n },\n \"missing_information\": [],\n \"risk_summary\": \"候选人期望明显高于内部同级平均水平\",\n \"priority_issues\": [\n \"候选人期望明显高于内部同级平均水平\"\n ],\n \"next_action\": \"按 42000 左右准备定薪审批材料，并同步说明 band、市场和内部公平依据。\",\n \"message_draft\": \"周子涵 的期望薪资与岗位 band、市场分位及内部参考已完成比对，本次属于“正式建议”，建议 建议按 band 中高位定薪。\",\n \"record_update\": {\n \"candidate_name\": \"周子涵\",\n \"target_role\": \"高级用户增长产品经理\",\n \"suggested_base\": 42000,\n \"recommendation_strength\": \"正式建议\"\n },\n \"data_sources_used\": {\n \"has_band\": true,\n \"has_paid_survey_data\": true,\n \"has_internal_reference\": true,\n \"has_budget\": true,\n \"has_current_pay\": true,\n \"has_public_market_signal\": true\n },\n \"compliance_warning_if_any\": []\n}\n\nFile v0.5.0:assets/generated-band-sample/band-offer-review-output.json\n\n{\n \"normalized_data\": {\n \"meta\": {\n \"workflow\": \"review_compensation_band_and_offer\",\n \"prepared_by\": \"HRBP\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\"\n },\n \"position\": {\n \"job_title\": \"高级用户增长产品经理\",\n \"job_family\": \"产品\",\n \"level\": \"P7\",\n \"city\": \"上海\"\n },\n \"band\": {\n \"currency\": \"CNY\",\n \"monthly_base_min\": 32000,\n \"monthly_base_mid\": 38000,\n \"monthly_base_max\": 45000\n },\n \"market_benchmark\": {\n \"sample_scope\": \"上海 互联网 / 产品增长 / P7\",\n \"p25\": 34000,\n \"p50\": 39000,\n \"p75\": 46000,\n \"notes\": \"市场样本以近 12 个月互联网增长产品岗位为主，头部平台给价更高。\"\n },\n \"candidate\": {\n \"candidate_name\": \"周子涵\",\n \"current_title\": \"增长产品负责人\",\n \"current_company\": \"某内容平台\",\n \"current_monthly_base\": 36000,\n \"expected_monthly_base\": 42000,\n \"target_role_reason\": \"有会员增长、增长实验和跨团队主导经验，业务方反馈较强，属于重点候选人。\"\n },\n \"internal_reference\": {\n \"same_level_employees\": [\n {\n \"employee_name\": \"A\",\n \"monthly_base\": 36500,\n \"note\": \"P7，增长产品，司龄 2 年\"\n },\n {\n \"employee_name\": \"B\",\n \"monthly_base\": 38800,\n \"note\": \"P7，用户增长，司龄 1 年\"\n },\n {\n \"employee_name\": \"C\",\n \"monthly_base\": 41000,\n \"note\": \"P7，核心增长岗，历史调薪后\"\n }\n ]\n }\n },\n \"missing_information\": [\n \"缺少预算范围\"\n ],\n \"risk_summary\": \"候选人期望明显高于内部同级平均水平\",\n \"priority_issues\": [\n \"候选人期望明显高于内部同级平均水平\"\n ],\n \"next_action\": \"先补齐 缺少预算范围，再决定是否进入正式定薪审批。\",\n \"message_draft\": \"周子涵 的期望薪资与岗位 band、市场分位及内部参考已完成比对，本次属于“弱建议”，建议 建议按 band 中高位定薪。\",\n \"record_update\": {\n \"candidate_name\": \"周子涵\",\n \"target_role\": \"高级用户增长产品经理\",\n \"suggested_base\": 42000,\n \"recommendation_strength\": \"弱建议\"\n },\n \"data_sources_used\": {\n \"has_band\": true,\n \"has_paid_survey_data\": true,\n \"has_internal_reference\": true,\n \"has_budget\": false,\n \"has_current_pay\": true,\n \"has_public_market_signal\": false\n },\n \"compliance_warning_if_any\": []\n}\n\nFile v0.5.0:assets/generated-sample/payroll-filing-precheck-output.json\n\n{\n \"normalized_data\": {\n \"meta\": {\n \"workflow\": \"precheck_payroll_filing\",\n \"prepared_by\": \"薪酬专员\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"payroll_month\": \"2026-04\"\n },\n \"employees\": [\n {\n \"employee_name\": \"王浩\",\n \"employee_id\": \"E001\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6222********1234\",\n \"id_number\": \"3101********1234\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 28500,\n \"social_base\": 28300,\n \"housing_fund_base\": 28700,\n \"special_additional_deduction\": 2000\n },\n {\n \"employee_name\": \"李茜\",\n \"employee_id\": \"E002\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"\",\n \"id_number\": \"3101********5678\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 19800,\n \"social_base\": 19800,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"陈航\",\n \"employee_id\": \"E003\",\n \"employment_status\": \"left\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********8888\",\n \"id_number\": \"3101********0001\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": false,\n \"salary_taxable_income\": 0,\n \"social_base\": 23000,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"赵琳\",\n \"employee_id\": \"E004\",\n \"employment_status\": \"active\",\n \"city\": \"深圳\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********9999\",\n \"id_number\": \"\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 32000,\n \"social_base\": 38000,\n \"housing_fund_base\": 38000,\n \"special_additional_deduction\": 1500\n },\n {\n \"employee_name\": \"孙捷\",\n \"employee_id\": \"E005\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"杭州某科技有限公司\",\n \"bank_account\": \"6217********7777\",\n \"id_number\": \"3301********3456\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": false,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 26500,\n \"social_base\": 0,\n \"housing_fund_base\": 26000,\n \"special_additional_deduction\": 1000\n }\n ],\n \"issue_count\": {\n \"high\": 5,\n \"medium\": 3,\n \"low\": 1\n }\n },\n \"missing_information\": [\n {\n \"employee_name\": \"李茜\",\n \"field_issue\": \"缺少工资银行卡信息\"\n },\n {\n \"employee_name\": \"李茜\",\n \"field_issue\": \"公积金需申报但缴存基数为 0\"\n },\n {\n \"employee_name\": \"赵琳\",\n \"field_issue\": \"缺少身份证号，存在个税申报风险\"\n }\n ],\n \"risk_summary\": \"本次申报前检查发现 4 名高风险人员，请优先补齐缺失字段、复核离职人员状态和申报主体/缴纳口径，再进入正式申报。\",\n \"priority_issues\": [\n {\n \"employee_name\": \"李茜\",\n \"issues\": [\n \"缺少工资银行卡信息\",\n \"公积金需申报但缴存基数为 0\"\n ]\n },\n {\n \"employee_name\": \"陈航\",\n \"issues\": [\n \"离职员工仍在本月申报名单中\"\n ]\n },\n {\n \"employee_name\": \"赵琳\",\n \"issues\": [\n \"缺少身份证号，存在个税申报风险\"\n ]\n },\n {\n \"employee_name\": \"孙捷\",\n \"issues\": [\n \"申报主体与本次发薪主体不一致\"\n ]\n }\n ],\n \"next_action\": \"先处理高风险人员和缺失字段，再进入正式申报。\",\n \"message_draft\": \"本次申报前检查发现 4 名高风险人员，请优先补齐缺失字段、复核离职人员状态和申报主体/缴纳口径，再进入正式申报。\",\n \"record_update\": {\n \"payroll_month\": \"2026-04\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"high_risk_count\": 4\n },\n \"compliance_warning_if_any\": [\n \"存在高风险申报问题，建议先修正后申报。\"\n ]\n}\n\nArchive v0.2.0: 13 files, 16788 bytes\n\nFiles: agents/openai.yaml (365b), assets/band-offer-review-input.sample.json (1509b), assets/generated-band-sample/band-offer-review-output.json (2241b), assets/generated-band-sample/band-offer-review.csv (262b), assets/generated-sample/payroll-filing-precheck-output.json (4697b), assets/generated-sample/payroll-filing-precheck.csv (978b), assets/payroll-precheck-input.sample.json (2814b), references/compensation-workflows.md (1092b), references/real-user-scenario.md (1479b), scripts/generate_band_offer_packet.js (7406b), scripts/generate_payroll_precheck_packet.js (9194b), SKILL.md (4331b), _meta.json (141b)\n\nFile v0.2.0:SKILL.md\n\n---\nname: hr-compensation-checks\ndescription: 帮中国 HR 做薪酬 band 校验、市场调研摘要、定薪建议，以及个税社保公积金申报前检查。 / Help HR teams in China with compensation band review, market benchmark summaries, offer pricing suggestions, and payroll filing prechecks.\nversion: 0.2.0\nmetadata:\n openclaw:\n homepage: https://github.com/Ashley-AIHR/hrskill-compensation-module\n envVars:\n - name: COMP_EXPORT_PATH\n required: false\n description: Optional local export path for filing check outputs.\n---\n\n# 薪酬判断与申报检查助手 / Compensation Decision and Filing Check Assistant\n\n当用户需要做两类薪酬工作时使用这个 skill：\n\n1. 薪酬判断：band、市场调研、offer 定薪建议\n2. 薪酬执行：个税、社保、公积金申报前检查\n\n它不是完整薪酬系统，而是一个把“高阶判断”和“落地检查”都结构化的小助手。 / Use this skill for both compensation decision work and payroll filing risk checks in China.\n\n## 当前 production-ready 场景\n\n1. `薪酬 band / 市场调研 / 定薪建议`\n2. `个税 / 社保 / 公积金申报前检查`\n\n这两个场景分别解决两类问题：\n\n1. 第一类解决“值多少钱、怎么定更合理”\n2. 第二类解决“报之前有哪些坑、哪些风险要先排”\n\n## 统一输出结构\n\n处理这类薪酬检查任务时，始终产出：\n\n```text\nnormalized_data\nmissing_information\nrisk_summary\npriority_issues\nnext_action\nmessage_draft\nrecord_update\ncompliance_warning_if_any\n```\n\n要求：\n\n1. `normalized_data` 要清楚列出人员、申报主体、申报地、基数和扣除信息。\n2. `missing_information` 要直接指出缺什么字段、缺在哪一类人员上。\n3. `risk_summary` 要优先写申报失败风险和合规风险。\n4. `priority_issues` 要按高、中、低分级。\n5. `next_action` 必须是 HR 今天可以执行的动作。\n6. `message_draft` 默认写成给内部协作方的数据追回或风险说明话术。\n7. `record_update` 适合写回申报 tracker 或月度薪酬待办表。\n\n## 当前 production-ready workflows\n\n### `review_compensation_band_and_offer`\n\n触发：\n\n1. HR 准备做 offer 定薪\n2. HR 想看候选人期望与 band、市场分位、内部公平是否匹配\n3. HR 想给老板准备定薪建议说明\n\n典型输入：\n\n1. 岗位职级与岗位族\n2. band 最低值、中位值、最高值\n3. 市场调研分位点\n4. 候选人当前薪资与期望薪资\n5. 内部同岗参考\n\n典型输出：\n\n1. band 位置判断\n2. 市场对标摘要\n3. 定薪建议\n4. 风险说明\n5. 给业务/老板的摘要\n6. 可下载的分析报告、CSV、JSON\n\n如果在本仓库本地运行，使用：\n\n```text\nnode scripts/generate_band_offer_packet.js \n```\n\n示例输入见 [assets/band-offer-review-input.sample.json](assets/band-offer-review-input.sample.json)。\n\n### `precheck_payroll_filing`\n\n触发：\n\n1. 月度工资已经核完，准备进入个税、社保、公积金申报\n2. HR 想先看有没有漏人、错基数、错申报地、错主体、专项附加扣除异常\n\n典型输入：\n\n1. 员工薪酬明细\n2. 个税申报字段\n3. 社保、公积金申报字段\n4. 员工状态与法人主体信息\n\n典型输出：\n\n1. 高风险问题清单\n2. 缺失字段清单\n3. 申报前待办\n4. 内部说明稿\n5. 可下载的检查报告、CSV、JSON\n\n如果在本仓库本地运行，使用：\n\n```text\nnode scripts/generate_payroll_precheck_packet.js \n```\n\n示例输入见 [assets/payroll-precheck-input.sample.json](assets/payroll-precheck-input.sample.json)。\n\n## 工作原则\n\n1. 做薪酬判断时，先看 band、市场和内部公平，再看单一薪资数字。\n2. 做申报检查时，优先检查申报失败风险，而不是追求复杂表达。\n3. 优先发现“漏人、错城市、错主体、错基数、缺专项附加扣除”。\n4. 如果只能做一件事，先把高风险问题按人列清楚。\n5. 不自动给出法律结论，但要明确提示合规风险。\n6. 如果用户给了自己公司的口径或 band 规则，优先遵循用户口径。\n\n## 参考资料\n\n1. [references/compensation-workflows.md](references/compensation-workflows.md)\n2. [references/real-user-scenario.md](references/real-user-scenario.md)\n\nFile v0.2.0:_meta.json\n\n{\n \"ownerId\": \"kn7cfgqtq1167ctj7rfp8cg3yn840js9\",\n \"slug\": \"hr-compensation-checks\",\n \"version\": \"0.2.0\",\n \"publishedAt\": 1779134344871\n}\n\nFile v0.2.0:references/compensation-workflows.md\n\n# 中国 HR 薪酬高频工作流\n\n这个 skill 当前只先做一个场景，但背后的工作流语境来自中国 HR 常见的薪酬操作链路。\n\n## 常见月度链路\n\n1. 人员异动确认\n2. 考勤、绩效、补发补扣等数据收集\n3. 算薪\n4. 差异复核\n5. 个税申报\n6. 社保申报\n7. 公积金汇缴\n8. 发薪与留痕\n\n## 当前最适合 AI 的两个切入点\n\n### 1. 薪酬判断\n\n包括：\n\n1. 薪酬 band 校验\n2. 市场调研摘要\n3. 定薪建议\n\n这类工作适合做“高阶判断型 Skill”，因为它很像资深 HR 脑子里的隐性判断。\n\n### 2. 申报前检查\n\n第一版不做完整算薪，而做：\n\n1. `band / 调研 / 定薪建议`\n2. `申报前检查`\n\n原因：\n\n1. 一个负责专业感与判断感\n2. 一个负责落地感与风险感\n3. 两者合在一起，才更像真实中国薪酬模块\n\n## 当前最应该优先识别的问题\n\n1. 人员漏报\n2. 离职人员仍在申报名单\n3. 申报主体错误\n4. 缴纳地错误\n5. 社保、公积金基数异常\n6. 专项附加扣除信息缺失或异常\n7. 银行卡或身份证号缺失\n\nFile v0.2.0:references/real-user-scenario.md\n\n# Real User Scenario\n\n## 推荐第一生产场景\n\n`月末准备做个税、社保、公积金申报，HR 想先做一轮检查`\n\n这非常真实，因为：\n\n1. 月度薪酬数据总会有缺口\n2. 申报前最后一轮检查非常耗 HR 时间\n3. 真正让 HR 紧张的不是“填表”，而是“怕申报失败或错报”\n\n## 典型触发\n\nHR 或薪酬专员会说：\n\n1. “这是本月申报名单，帮我看看有没有高风险问题。”\n2. “个税、社保、公积金申报前先帮我排一下雷。”\n3. “哪些人缺字段，哪些人基数或主体有问题，给我一个待办清单。”\n\n## 最低有用输出\n\n1. 高风险问题摘要\n2. 按人员列出的问题明细\n3. 缺失字段清单\n4. 内部协作提醒话术\n5. 可回写的检查记录\n\n## 推荐第二生产场景\n\n`准备发 offer 或做关键岗位定薪，HR 想先看 band、市场和内部公平`\n\n这也非常真实，因为：\n\n1. 薪酬判断并不是拍脑袋\n2. 定薪最难的是把市场、band、候选人期望和内部公平放在一起看\n3. 这是最适合做“认知型 + 传播型”薪酬内容的场景\n\n典型触发：\n\n1. “这个候选人期望 40k，到底能不能给？”\n2. “帮我看看这个 offer 是在 band 里什么位置。”\n3. “把市场分位、内部参考和定薪建议整理成一版摘要。”\n\n最低有用输出：\n\n1. band 位置判断\n2. 市场对标摘要\n3. offer 定薪建议\n4. 风险说明\n5. 给业务/老板看的说明稿\n\nFile v0.2.0:assets/band-offer-review-input.sample.json\n\n{\n \"meta\": {\n \"workflow\": \"review_compensation_band_and_offer\",\n \"prepared_by\": \"HRBP\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\"\n },\n \"position\": {\n \"job_title\": \"高级用户增长产品经理\",\n \"job_family\": \"产品\",\n \"level\": \"P7\",\n \"city\": \"上海\"\n },\n \"band\": {\n \"currency\": \"CNY\",\n \"monthly_base_min\": 32000,\n \"monthly_base_mid\": 38000,\n \"monthly_base_max\": 45000\n },\n \"market_benchmark\": {\n \"sample_scope\": \"上海 互联网 / 产品增长 / P7\",\n \"p25\": 34000,\n \"p50\": 39000,\n \"p75\": 46000,\n \"notes\": \"市场样本以近 12 个月互联网增长产品岗位为主，头部平台给价更高。\"\n },\n \"candidate\": {\n \"candidate_name\": \"周子涵\",\n \"current_title\": \"增长产品负责人\",\n \"current_company\": \"某内容平台\",\n \"current_monthly_base\": 36000,\n \"expected_monthly_base\": 42000,\n \"target_role_reason\": \"有会员增长、增长实验和跨团队主导经验，业务方反馈较强，属于重点候选人。\"\n },\n \"internal_reference\": {\n \"same_level_employees\": [\n {\n \"employee_name\": \"A\",\n \"monthly_base\": 36500,\n \"note\": \"P7，增长产品，司龄 2 年\"\n },\n {\n \"employee_name\": \"B\",\n \"monthly_base\": 38800,\n \"note\": \"P7，用户增长，司龄 1 年\"\n },\n {\n \"employee_name\": \"C\",\n \"monthly_base\": 41000,\n \"note\": \"P7，核心增长岗，历史调薪后\"\n }\n ]\n }\n}\n\nFile v0.2.0:assets/generated-band-sample/band-offer-review-output.json\n\n{\n \"normalized_data\": {\n \"meta\": {\n \"workflow\": \"review_compensation_band_and_offer\",\n \"prepared_by\": \"HRBP\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\"\n },\n \"position\": {\n \"job_title\": \"高级用户增长产品经理\",\n \"job_family\": \"产品\",\n \"level\": \"P7\",\n \"city\": \"上海\"\n },\n \"band\": {\n \"currency\": \"CNY\",\n \"monthly_base_min\": 32000,\n \"monthly_base_mid\": 38000,\n \"monthly_base_max\": 45000\n },\n \"market_benchmark\": {\n \"sample_scope\": \"上海 互联网 / 产品增长 / P7\",\n \"p25\": 34000,\n \"p50\": 39000,\n \"p75\": 46000,\n \"notes\": \"市场样本以近 12 个月互联网增长产品岗位为主，头部平台给价更高。\"\n },\n \"candidate\": {\n \"candidate_name\": \"周子涵\",\n \"current_title\": \"增长产品负责人\",\n \"current_company\": \"某内容平台\",\n \"current_monthly_base\": 36000,\n \"expected_monthly_base\": 42000,\n \"target_role_reason\": \"有会员增长、增长实验和跨团队主导经验，业务方反馈较强，属于重点候选人。\"\n },\n \"internal_reference\": {\n \"same_level_employees\": [\n {\n \"employee_name\": \"A\",\n \"monthly_base\": 36500,\n \"note\": \"P7，增长产品，司龄 2 年\"\n },\n {\n \"employee_name\": \"B\",\n \"monthly_base\": 38800,\n \"note\": \"P7，用户增长，司龄 1 年\"\n },\n {\n \"employee_name\": \"C\",\n \"monthly_base\": 41000,\n \"note\": \"P7，核心增长岗，历史调薪后\"\n }\n ]\n }\n },\n \"missing_information\": [],\n \"risk_summary\": \"候选人期望明显高于内部同级平均水平\",\n \"priority_issues\": [\n \"候选人期望明显高于内部同级平均水平\"\n ],\n \"next_action\": \"按 42000 左右准备定薪审批材料，并同步说明 band 与市场依据。\",\n \"message_draft\": \"周子涵 的期望薪资与岗位 band、市场分位已完成比对，建议 建议按 band 中高位定薪。\",\n \"record_update\": {\n \"candidate_name\": \"周子涵\",\n \"target_role\": \"高级用户增长产品经理\",\n \"suggested_base\": 42000\n },\n \"compliance_warning_if_any\": []\n}\n\nFile v0.2.0:assets/generated-sample/payroll-filing-precheck-output.json\n\n{\n \"normalized_data\": {\n \"meta\": {\n \"workflow\": \"precheck_payroll_filing\",\n \"prepared_by\": \"薪酬专员\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"payroll_month\": \"2026-04\"\n },\n \"employees\": [\n {\n \"employee_name\": \"王浩\",\n \"employee_id\": \"E001\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6222********1234\",\n \"id_number\": \"3101********1234\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 28500,\n \"social_base\": 28300,\n \"housing_fund_base\": 28700,\n \"special_additional_deduction\": 2000\n },\n {\n \"employee_name\": \"李茜\",\n \"employee_id\": \"E002\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"\",\n \"id_number\": \"3101********5678\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 19800,\n \"social_base\": 19800,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"陈航\",\n \"employee_id\": \"E003\",\n \"employment_status\": \"left\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********8888\",\n \"id_number\": \"3101********0001\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": false,\n \"salary_taxable_income\": 0,\n \"social_base\": 23000,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"赵琳\",\n \"employee_id\": \"E004\",\n \"employment_status\": \"active\",\n \"city\": \"深圳\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********9999\",\n \"id_number\": \"\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 32000,\n \"social_base\": 38000,\n \"housing_fund_base\": 38000,\n \"special_additional_deduction\": 1500\n },\n {\n \"employee_name\": \"孙捷\",\n \"employee_id\": \"E005\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"杭州某科技有限公司\",\n \"bank_account\": \"6217********7777\",\n \"id_number\": \"3301********3456\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": false,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 26500,\n \"social_base\": 0,\n \"housing_fund_base\": 26000,\n \"special_additional_deduction\": 1000\n }\n ],\n \"issue_count\": {\n \"high\": 5,\n \"medium\": 3,\n \"low\": 1\n }\n },\n \"missing_information\": [\n {\n \"employee_name\": \"李茜\",\n \"field_issue\": \"缺少工资银行卡信息\"\n },\n {\n \"employee_name\": \"李茜\",\n \"field_issue\": \"公积金需申报但缴存基数为 0\"\n },\n {\n \"employee_name\": \"赵琳\",\n \"field_issue\": \"缺少身份证号，存在个税申报风险\"\n }\n ],\n \"risk_summary\": \"本次申报前检查发现 4 名高风险人员，请优先补齐缺失字段、复核离职人员状态和申报主体/缴纳口径，再进入正式申报。\",\n \"priority_issues\": [\n {\n \"employee_name\": \"李茜\",\n \"issues\": [\n \"缺少工资银行卡信息\",\n \"公积金需申报但缴存基数为 0\"\n ]\n },\n {\n \"employee_name\": \"陈航\",\n \"issues\": [\n \"离职员工仍在本月申报名单中\"\n ]\n },\n {\n \"employee_name\": \"赵琳\",\n \"issues\": [\n \"缺少身份证号，存在个税申报风险\"\n ]\n },\n {\n \"employee_name\": \"孙捷\",\n \"issues\": [\n \"申报主体与本次发薪主体不一致\"\n ]\n }\n ],\n \"next_action\": \"先处理高风险人员和缺失字段，再进入正式申报。\",\n \"message_draft\": \"本次申报前检查发现 4 名高风险人员，请优先补齐缺失字段、复核离职人员状态和申报主体/缴纳口径，再进入正式申报。\",\n \"record_update\": {\n \"payroll_month\": \"2026-04\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"high_risk_count\": 4\n },\n \"compliance_warning_if_any\": [\n \"存在高风险申报问题，建议先修正后申报。\"\n ]\n}\n\nFile v0.2.0:assets/payroll-precheck-input.sample.json\n\n{\n \"meta\": {\n \"workflow\": \"precheck_payroll_filing\",\n \"prepared_by\": \"薪酬专员\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"payroll_month\": \"2026-04\"\n },\n \"employees\": [\n {\n \"employee_name\": \"王浩\",\n \"employee_id\": \"E001\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6222********1234\",\n \"id_number\": \"3101********1234\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 28500,\n \"social_base\": 28300,\n \"housing_fund_base\": 28700,\n \"special_additional_deduction\": 2000\n },\n {\n \"employee_name\": \"李茜\",\n \"employee_id\": \"E002\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"\",\n \"id_number\": \"3101********5678\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 19800,\n \"social_base\": 19800,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"陈航\",\n \"employee_id\": \"E003\",\n \"employment_status\": \"left\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********8888\",\n \"id_number\": \"3101********0001\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": false,\n \"salary_taxable_income\": 0,\n \"social_base\": 23000,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"赵琳\",\n \"employee_id\": \"E004\",\n \"employment_status\": \"active\",\n \"city\": \"深圳\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********9999\",\n \"id_number\": \"\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 32000,\n \"social_base\": 38000,\n \"housing_fund_base\": 38000,\n \"special_additional_deduction\": 1500\n },\n {\n \"employee_name\": \"孙捷\",\n \"employee_id\": \"E005\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"杭州某科技有限公司\",\n \"bank_account\": \"6217********7777\",\n \"id_number\": \"3301********3456\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": false,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 26500,\n \"social_base\": 0,\n \"housing_fund_base\": 26000,\n \"special_additional_deduction\": 1000\n }\n ]\n}\n\nFile v0.2.0:agents/openai.yaml\n\ninterface:\n display_name: \"薪酬判断与申报检查助手 / Compensation Decision Assistant\"\n short_description: \"band、定薪、申报前检查 / Band, offer, and filing checks\"\n default_prompt: \"使用 $hr-compensation-checks 帮我做薪酬 band / 定薪判断，或者个税、社保、公积金申报前检查，优先输出结论、风险和待办。\"\n\nArchive v0.1.0: 9 files, 10375 bytes\n\nFiles: agents/openai.yaml (354b), assets/generated-sample/payroll-filing-precheck-output.json (4697b), assets/generated-sample/payroll-filing-precheck.csv (978b), assets/payroll-precheck-input.sample.json (2814b), references/compensation-workflows.md (791b), references/real-user-scenario.md (778b), scripts/generate_payroll_precheck_packet.js (9194b), SKILL.md (3256b), _meta.json (141b)\n\nFile v0.1.0:SKILL.md\n\n---\nname: hr-compensation-checks\ndescription: 帮中国 HR 在个税、社保、公积金申报前做数据检查、缺口定位、风险摘要和待办输出。 / Help HR teams in China check payroll filing data before IIT, social insurance, and housing fund submission.\nversion: 0.1.0\nmetadata:\n openclaw:\n homepage: https://github.com/Ashley-AIHR/hrskill-compensation-module\n envVars:\n - name: COMP_EXPORT_PATH\n required: false\n description: Optional local export path for filing check outputs.\n---\n\n# 薪酬申报检查助手 / Payroll Filing Check Assistant\n\n当用户需要在个税、社保、公积金申报前快速发现数据缺口、识别高风险错误、整理待办事项时使用这个 skill。它不是完整算薪系统，而是一个帮 HR 在申报前“先排雷”的执行型助手。 / Use this skill when the user needs a fast pre-filing check for payroll, IIT, social insurance, and housing fund data in China.\n\n## 当前最完整场景\n\n`个税 / 社保 / 公积金申报前检查`\n\n这个场景最适合第一版，因为它：\n\n1. 高频\n2. 真实\n3. 风险感强\n4. 不需要一开始就做完整算薪引擎\n\n## 统一输出结构\n\n处理这类薪酬检查任务时，始终产出：\n\n```text\nnormalized_data\nmissing_information\nrisk_summary\npriority_issues\nnext_action\nmessage_draft\nrecord_update\ncompliance_warning_if_any\n```\n\n要求：\n\n1. `normalized_data` 要清楚列出人员、申报主体、申报地、基数和扣除信息。\n2. `missing_information` 要直接指出缺什么字段、缺在哪一类人员上。\n3. `risk_summary` 要优先写申报失败风险和合规风险。\n4. `priority_issues` 要按高、中、低分级。\n5. `next_action` 必须是 HR 今天可以执行的动作。\n6. `message_draft` 默认写成给内部协作方的数据追回或风险说明话术。\n7. `record_update` 适合写回申报 tracker 或月度薪酬待办表。\n\n## 当前 production-ready workflow\n\n### `precheck_payroll_filing`\n\n触发：\n\n1. 月度工资已经核完，准备进入个税、社保、公积金申报\n2. HR 想先看有没有漏人、错基数、错申报地、错主体、专项附加扣除异常\n\n典型输入：\n\n1. 员工薪酬明细\n2. 个税申报字段\n3. 社保、公积金申报字段\n4. 员工状态与法人主体信息\n\n典型输出：\n\n1. 高风险问题清单\n2. 缺失字段清单\n3. 申报前待办\n4. 内部说明稿\n5. 可下载的检查报告、CSV、JSON\n\n如果在本仓库本地运行，使用：\n\n```text\nnode scripts/generate_payroll_precheck_packet.js \n```\n\n示例输入见 [assets/payroll-precheck-input.sample.json](assets/payroll-precheck-input.sample.json)。\n\n## 工作原则\n\n1. 优先检查申报失败风险，而不是追求复杂表达。\n2. 优先发现“漏人、错城市、错主体、错基数、缺专项附加扣除”。\n3. 如果只能做一件事，先把高风险问题按人列清楚。\n4. 不自动给出法律结论，但要明确提示合规风险。\n5. 如果用户给了自己公司的检查口径，优先遵循用户口径。\n\n## 参考资料\n\n1. [references/compensation-workflows.md](references/compensation-workflows.md)\n2. [references/real-user-scenario.md](references/real-user-scenario.md)\n\nFile v0.1.0:_meta.json\n\n{\n \"ownerId\": \"kn7cfgqtq1167ctj7rfp8cg3yn840js9\",\n \"slug\": \"hr-compensation-checks\",\n \"version\": \"0.1.0\",\n \"publishedAt\": 1779134171372\n}\n\nFile v0.1.0:references/compensation-workflows.md\n\n# 中国 HR 薪酬高频工作流\n\n这个 skill 当前只先做一个场景，但背后的工作流语境来自中国 HR 常见的薪酬操作链路。\n\n## 常见月度链路\n\n1. 人员异动确认\n2. 考勤、绩效、补发补扣等数据收集\n3. 算薪\n4. 差异复核\n5. 个税申报\n6. 社保申报\n7. 公积金汇缴\n8. 发薪与留痕\n\n## 当前最适合 AI 的切入点\n\n第一版不做完整算薪，而做：\n\n`申报前检查`\n\n原因：\n\n1. 场景清楚\n2. 风险集中\n3. 很适合做“发现问题 -> 摘要风险 -> 列待办”\n\n## 当前最应该优先识别的问题\n\n1. 人员漏报\n2. 离职人员仍在申报名单\n3. 申报主体错误\n4. 缴纳地错误\n5. 社保、公积金基数异常\n6. 专项附加扣除信息缺失或异常\n7. 银行卡或身份证号缺失\n\nFile v0.1.0:references/real-user-scenario.md\n\n# Real User Scenario\n\n## 推荐第一生产场景\n\n`月末准备做个税、社保、公积金申报，HR 想先做一轮检查`\n\n这非常真实，因为：\n\n1. 月度薪酬数据总会有缺口\n2. 申报前最后一轮检查非常耗 HR 时间\n3. 真正让 HR 紧张的不是“填表”，而是“怕申报失败或错报”\n\n## 典型触发\n\nHR 或薪酬专员会说：\n\n1. “这是本月申报名单，帮我看看有没有高风险问题。”\n2. “个税、社保、公积金申报前先帮我排一下雷。”\n3. “哪些人缺字段，哪些人基数或主体有问题，给我一个待办清单。”\n\n## 最低有用输出\n\n1. 高风险问题摘要\n2. 按人员列出的问题明细\n3. 缺失字段清单\n4. 内部协作提醒话术\n5. 可回写的检查记录\n\nFile v0.1.0:assets/generated-sample/payroll-filing-precheck-output.json\n\n{\n \"normalized_data\": {\n \"meta\": {\n \"workflow\": \"precheck_payroll_filing\",\n \"prepared_by\": \"薪酬专员\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"payroll_month\": \"2026-04\"\n },\n \"employees\": [\n {\n \"employee_name\": \"王浩\",\n \"employee_id\": \"E001\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6222********1234\",\n \"id_number\": \"3101********1234\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 28500,\n \"social_base\": 28300,\n \"housing_fund_base\": 28700,\n \"special_additional_deduction\": 2000\n },\n {\n \"employee_name\": \"李茜\",\n \"employee_id\": \"E002\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"\",\n \"id_number\": \"3101********5678\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 19800,\n \"social_base\": 19800,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"陈航\",\n \"employee_id\": \"E003\",\n \"employment_status\": \"left\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********8888\",\n \"id_number\": \"3101********0001\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": false,\n \"salary_taxable_income\": 0,\n \"social_base\": 23000,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"赵琳\",\n \"employee_id\": \"E004\",\n \"employment_status\": \"active\",\n \"city\": \"深圳\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********9999\",\n \"id_number\": \"\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 32000,\n \"social_base\": 38000,\n \"housing_fund_base\": 38000,\n \"special_additional_deduction\": 1500\n },\n {\n \"employee_name\": \"孙捷\",\n \"employee_id\": \"E005\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"杭州某科技有限公司\",\n \"bank_account\": \"6217********7777\",\n \"id_number\": \"3301********3456\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": false,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 26500,\n \"social_base\": 0,\n \"housing_fund_base\": 26000,\n \"special_additional_deduction\": 1000\n }\n ],\n \"issue_count\": {\n \"high\": 5,\n \"medium\": 3,\n \"low\": 1\n }\n },\n \"missing_information\": [\n {\n \"employee_name\": \"李茜\",\n \"field_issue\": \"缺少工资银行卡信息\"\n },\n {\n \"employee_name\": \"李茜\",\n \"field_issue\": \"公积金需申报但缴存基数为 0\"\n },\n {\n \"employee_name\": \"赵琳\",\n \"field_issue\": \"缺少身份证号，存在个税申报风险\"\n }\n ],\n \"risk_summary\": \"本次申报前检查发现 4 名高风险人员，请优先补齐缺失字段、复核离职人员状态和申报主体/缴纳口径，再进入正式申报。\",\n \"priority_issues\": [\n {\n \"employee_name\": \"李茜\",\n \"issues\": [\n \"缺少工资银行卡信息\",\n \"公积金需申报但缴存基数为 0\"\n ]\n },\n {\n \"employee_name\": \"陈航\",\n \"issues\": [\n \"离职员工仍在本月申报名单中\"\n ]\n },\n {\n \"employee_name\": \"赵琳\",\n \"issues\": [\n \"缺少身份证号，存在个税申报风险\"\n ]\n },\n {\n \"employee_name\": \"孙捷\",\n \"issues\": [\n \"申报主体与本次发薪主体不一致\"\n ]\n }\n ],\n \"next_action\": \"先处理高风险人员和缺失字段，再进入正式申报。\",\n \"message_draft\": \"本次申报前检查发现 4 名高风险人员，请优先补齐缺失字段、复核离职人员状态和申报主体/缴纳口径，再进入正式申报。\",\n \"record_update\": {\n \"payroll_month\": \"2026-04\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"high_risk_count\": 4\n },\n \"compliance_warning_if_any\": [\n \"存在高风险申报问题，建议先修正后申报。\"\n ]\n}\n\nFile v0.1.0:assets/payroll-precheck-input.sample.json\n\n{\n \"meta\": {\n \"workflow\": \"precheck_payroll_filing\",\n \"prepared_by\": \"薪酬专员\",\n \"date\": \"2026-05-19\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"payroll_month\": \"2026-04\"\n },\n \"employees\": [\n {\n \"employee_name\": \"王浩\",\n \"employee_id\": \"E001\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6222********1234\",\n \"id_number\": \"3101********1234\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 28500,\n \"social_base\": 28300,\n \"housing_fund_base\": 28700,\n \"special_additional_deduction\": 2000\n },\n {\n \"employee_name\": \"李茜\",\n \"employee_id\": \"E002\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"\",\n \"id_number\": \"3101********5678\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 19800,\n \"social_base\": 19800,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"陈航\",\n \"employee_id\": \"E003\",\n \"employment_status\": \"left\",\n \"city\": \"上海\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********8888\",\n \"id_number\": \"3101********0001\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": false,\n \"salary_taxable_income\": 0,\n \"social_base\": 23000,\n \"housing_fund_base\": 0,\n \"special_additional_deduction\": 0\n },\n {\n \"employee_name\": \"赵琳\",\n \"employee_id\": \"E004\",\n \"employment_status\": \"active\",\n \"city\": \"深圳\",\n \"legal_entity\": \"上海某科技有限公司\",\n \"bank_account\": \"6217********9999\",\n \"id_number\": \"\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": true,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 32000,\n \"social_base\": 38000,\n \"housing_fund_base\": 38000,\n \"special_additional_deduction\": 1500\n },\n {\n \"employee_name\": \"孙捷\",\n \"employee_id\": \"E005\",\n \"employment_status\": \"active\",\n \"city\": \"上海\",\n \"legal_entity\": \"杭州某科技有限公司\",\n \"bank_account\": \"6217********7777\",\n \"id_number\": \"3301********3456\",\n \"tax_declaration\": true,\n \"social_insurance_declaration\": false,\n \"housing_fund_declaration\": true,\n \"salary_taxable_income\": 26500,\n \"social_base\": 0,\n \"housing_fund_base\": 26000,\n \"special_additional_deduction\": 1000\n }\n ]\n}\n\nFile v0.1.0:agents/openai.yaml\n\ninterface:\n display_name: \"薪酬申报检查助手 / Payroll Filing Check Assistant\"\n short_description: \"个税社保公积金申报前检查 / Precheck for payroll filings\"\n default_prompt: \"使用 $hr-compensation-checks 帮我检查个税、社保、公积金申报前的数据风险，优先输出高风险问题、待办和内部说明稿。\"","readmeExcerpt":"Skill: Compensation Repo Owner: ashley-aihr Summary: 做定薪判断，也先把申报前风险挑出来 / Price offers and catch filing risks Tags: china:0.2.0, compensation:0.2.0, hr:0.2.0, latest:0.5.0, payroll:0.2.0 Version history: v0.5.0 | 2026-05-18T20:34:48.346Z | auto **Summary:** Introduces dynamic market data handling, clearer output protocols, and improved decision logic for compensation and payroll checks. - Added support for dynamic mar","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"normalized_data\ndecision_summary\ndecision_basis\nmissing_information\nrisk_summary\npriority_issues\nnext_action\nmessage_draft\nrecord_update\nhuman_confirmation_needed\ncompliance_warning_if_any"},{"language":"text","snippet":"job_family\njob_level\nband_min\nband_mid\nband_max\nmarket_p25\nmarket_p50\nmarket_p75\ncandidate_current_pay\ncandidate_expected_pay\ninternal_peer_reference\nbudget_range"},{"language":"text","snippet":"official_policy\npublic_market_signal\npaid_survey_data\ninternal_company_data\ncandidate_total_comp_context"},{"language":"text","snippet":"node scripts/generate_band_offer_packet.js "},{"language":"text","snippet":"employee_name\nemployee_status\nlegal_entity\nwork_city\nfiling_city\nbank_account_status\nid_number_status\ntaxable_income\nsocial_base\nhousing_fund_base\nspecial_deduction_status"},{"language":"text","snippet":"node scripts/generate_payroll_precheck_packet.js "}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: hr-compensation-checks\ndescription: 帮 HR 做定薪判断、band 对标、市场调研摘要，以及个税社保公积金申报前检查，先看值不值，再看会不会出风险。 / Help HR teams with compensation review, band and market checks, and payroll filing prechecks.\nversion: 0.5.0\nmetadata:\n openclaw:\n homepage: https://github.com/Ashley-AIHR/hrskill-compensation-module\n envVars:\n - name: COMP_EXPORT_PATH\n required: false\n description: Optional local export path for filing check outputs.\n---\n\n# 定薪与申报检查助手 / Compensation Decision Assistant\n\n当用户在处理两类薪酬工作时使用这个 skill：\n\n1. 定薪判断：band、市场调研、内部公平、offer 建议\n2. 申报检查：个税、社保、公积金申报前排雷\n\n目标不是手算工资，而是输出：\n\n1. 结论\n2. 依据\n3. 风险\n4. 待办\n5. 可直接发给内部协作方的说明\n\n如果用户第一次使用或输入很乱，先读 [references/real-user-scenario.md](references/real-user-scenario.md)。\n如果需要工作流背景，读 [references/compensation-workflows.md](references/compensation-workflows.md)。\n如果需要最新政策、城市口径和系统操作依据，读 [references/china-compensation-policy-kb-2026.md](references/china-compensation-policy-kb-2026.md)。\n如果需要理解动态市场数据怎么分层、哪些能当正式依据，读 [references/dynamic-market-data-architecture.md](references/dynamic-market-data-architecture.md)。\n\n## 路由规则\n\n根据输入内容路由到下面动作之一：\n\n1. `review_compensation_band_and_offer`\n 触发条件：输入里有 band、市场分位、候选人期望、内部参考、预算中的任意组合。\n2. `precheck_payroll_filing`\n 触发条件：输入里有个税、社保、公积金申报字段，或月度申报名单、员工状态、主体信息。\n\n如果用户不知道该选哪个动作：\n\n1. 有申报名单、基数、主体、缴纳地，就走 `precheck_payroll_filing`\n2. 有 band、市场分位、候选人期望，就走 `review_compensation_band_and_offer`\n\n对 `review_compensation_band_and_offer`，必须区分：\n\n1. `official_policy`\n2. `public_market_signal`\n3. `paid_survey_data`\n4. `internal_company_data`\n\n如果只有 `public_market_signal`，不允许把结论写成正式定薪建议。\n\n## 输出协议\n\n处理任意薪酬场景时，始终输出：\n\n```text\nnormalized_data\ndecision_summary\ndecision_basis\nmissing_information\nrisk_summary\npriority_issues\nnext_action\nmessage_draft\nrecord_update\nhuman_confirmation_needed\ncompliance_warning_if_any\n```\n\n要求：\n\n1. `decision_summary` 必须先回答“怎么定”或“能不能报”。\n2. `decision_basis` 必须把 band、市场、内部参考或申报依据讲清楚。\n3. `missing_information` 只写真正影响判断或申报的缺口。\n4. `risk_summary` 优先写申报失败风险、内部公平风险、预算风险。\n5. `priority_issues` 必须按高、中、低排序。\n6. `next_action` 必须是 HR 今天能做的动作。\n7. `message_draft` 默认写给业务负责人、薪酬同事或数据提供方。\n8. `human_confirmation_needed` 必须写清楚还要谁确认什么。\n9. 对定薪场景，必须标明本次结论属于 `正式建议`、`弱建议` 还是 `仅市场信号判断`。\n\n## 动作要求\n\n### `review_compensation_band_and_offer`\n\n至少抽取：\n\n```text\njob_family\njob_level\nband_min\nband_mid\nband_max\nmarket_p25\nmarket_p50\nmarket_p75\ncandidate_current_pay\ncandidate_expected_pay\ninternal_peer_reference\nbudget_range\n```\n\n并优先识别：\n\n```text\nofficial_policy\npublic_market_signal\npaid_survey_data\ninternal_company_data\ncandidate_total_comp_context\n```\n\n结果优先顺序：\n\n1. 建议怎么定\n2. 为什么这么定\n3. 内部公平或预算风险\n4. 怎么和业务解释\n5. 还需要谁确认\n\n判断规则：\n\n1. 同时具备 `internal_company_data + paid_survey_data + candidate_current_pay_or_total_comp + budget_range` 时，才可给 `正式建议`\n2. 只有 `public_market_signal` 时，只能给 `市场信号判断`\n3. 缺少 `band` 或 `internal_company_data` 时，不得假装能完成内部公平判断\n4. 缺少 `budget_range` 时，不得假装能完成审批级建议\n5. 缺少 `candidate_current_pay` 或总包口径时，要主动降低结论强度\n\n如果需要文件产出，运行：\n\n```text\nnode scripts/generate_band_offer_packet.js \n```\n\n示"},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn7cfgqtq1167ctj7rfp8cg3yn840js9\",\n \"slug\": \"hr-compensation-checks\",\n \"version\": \"0.5.0\",\n \"publishedAt\": 1779136488346\n}"},{"path":"references/china-compensation-policy-kb-2026.md","content":"# 中国薪酬申报与定薪知识库\n\n更新时间：2026-05-19\n\n这份文件只收录两类内容：\n\n1. 会随着时间、城市、系统流程变化的动态资料\n2. 可以直接支撑薪酬 skill 判断的政策与操作依据\n\n它不是完整政策汇编，而是给 skill 用的最小知识库。\n\n## 先给结论\n\n截至 2026-05-19，当前 repo 里原本并没有真正把这些动态资料接进去。\n\n最明显的缺口有 4 个：\n\n1. 没有按城市维护社保、公积金口径\n2. 没有按年度维护社保缴费工资申报周期\n3. 没有把个税扣缴端和 WEB 端的真实操作限制接进去\n4. 没有把“哪些数据能公开动态获取、哪些不能”说清楚\n\n所以如果这个 skill 要从 prototype 变成 professional-grade，至少要从这份知识库起步。\n\n## 一、社保年度缴费工资申报：这是真正会变的动态资料\n\n### 上海：2026 社保年度申报已经变化\n\n官方来源：\n\n1. 国家税务总局上海市税务局\n [关于开展2026社保年度用人单位社会保险缴费工资申报工作的通告](https://shanghai.chinatax.gov.cn/zcfw/zcfgk/sbf/202604/t480144.html)\n2. 国家税务总局上海市税务局\n [一图了解：上海市2026社保年度用人单位社会保险缴费工资申报](https://shanghai.chinatax.gov.cn/zcfw/tjss/202605/t480288.html)\n\n截至 2026-05-19，关键动态口径是：\n\n1. 申报时间：2026-05-01 至 2026-06-25\n2. 对应社保年度：2026-07 至 2027-06\n3. 用人单位要按 2025-01-01 至 2025-12-31 的上一自然年度月平均工资申报\n4. 上一年工作不满一年的职工，按工资总额除以实际工作月数计算\n5. 2026 年新招录职工，以起薪当月全月工资收入申报\n6. 申报渠道至少包括上海电子税务局、社保费管理客户端、办税服务厅\n\n这意味着：\n\n1. `precheck_payroll_filing` 不能只做“当月申报前检查”\n2. 还必须知道当前是不是处在“年度缴费工资申报窗口”\n3. 对上海场景，必须区分“月度申报前检查”和“年度基数申报检查”\n\n## 二、公积金：北京、深圳都不是静态规则\n\n### 北京：社保工资与公积金基数已经开始联动\n\n官方来源：\n\n1. 北京住房公积金管理中心\n [2025住房公积金年度缴存基数申报常见问题解答](https://gjj.beijing.gov.cn/web/zwfw5/1747335/1747336/743669918/index.html)\n2. 北京住房公积金管理中心\n [《关于2025住房公积金年度缴存有关问题的通知》政策解读](https://gjj.beijing.gov.cn/web/zwgk61/2024zcjd/743765478/index.html)\n3. 北京住房公积金管理中心\n [《关于用人单位和灵活就业人员申报2025年度社会保险费缴费工资（缴费基数）有关事项的通告》（住房公积金部分）政策解读](https://gjj.beijing.gov.cn/web/zwgk61/2024zcjd/743660449/)\n\n截至 2026-05-19，关键口径是：\n\n1. 2025 公积金年度为 2025-07-01 至 2026-06-30\n2. 缴存比例仍是 5% 至 12%\n3. 月缴存基数上限为 35811 元\n4. 自 2025-09-01 起，月缴存基数下限为 2540 元\n5. 领取基本生活费职工的下限为 1778 元\n6. 单位可授权公积金中心获取已向税务部门申报的社保缴费工资，作为核定公积金缴存基数的“上年月均工资”\n\n这意味着：\n\n1. 北京场景下，公积金不能完全当成一套独立口径\n2. skill 需要知道“社保年度申报数据是否已经可供授权获取”\n3. 如果企业是在 6 月到 7 月切换窗口期，系统要提醒“缴存基数申报”和“7 月汇缴名单确认”的顺序风险\n\n### 深圳：2026 年公积金规则也在变\n\n官方来源：\n\n1. 深圳政府在线\n [深圳新版住房公积金管理办法下月起施行](https://www.sz.gov.cn/cn/xxgk/zfxxgj/zwdt/content/post_12687780.html)\n2. 深圳市住房和建设局\n [缴存基数调整有什么要求？](https://zjj.sz.gov.cn/zcjzts/content/post_12322480.html)\n3. 深圳市住房公积金管理中心问答\n [个人缴存比例从2026年4月1日起就能申请调整，还是要等到7月1日才能调整？](https://zjj.sz.gov.cn/szszfhjsjwzgkml/szszfhjsjwzgkml/seztfw/zfly/wyw/ywzsk/content/post_12703688.html)\n\n截至 2026-05-19，关键口径是：\n\n1. 深圳新版《住房公积金管理办法》在 2026-04 起进入新阶段\n2. 每个住房公积金年度为当年 7 月 1 日至次年 6 月 30 日\n3. 职工可在单位缴存比例基础上，自愿申请提高个人缴存比例\n4. 调整后的个人缴存比例最高不超过 12%\n5. 在每个住房公积金年度内，职工可调整一次个人缴存比例\n\n这意味着：\n\n1. 深圳场景不只要检查缴存基数，还要检查“个人缴存比例是否已在年度内调整过”\n2. 如果把深圳用户当成和北京、上海完全同一套逻辑，会误判\n\n## 三、个税扣缴：真实工作不是“算税”，而是“系统约束 + 数据恢复 + 更正逻辑”\n\n官方来源：\n\n1. 国家税务总局上海市税务局\n [自然人扣缴端热点操作问答](https://shanghai.chinatax.gov.cn/jstax/ztzl/yshj/sycz/202512/t478537.html)\n2. 国家税务总局广东省税务局转发\n [自然人电子税务局WEB端扣缴业务等相关功能操作指南](https://guangdong.chinatax.gov.cn/gdsw/zqsw_tzgg/2020-11/18/content_75df0d6a19634d9596f0bffd81492a5c.shtml)\n\n截至 2026-05-19，对 skill 最有用的不是税率本身，而是这些操作型事实：\n\n1. 扣缴端数据丢失时，不是所有企业都能直接恢复\n2. 办税人员可能需要先申请开通“扣缴端数据下载”权限\n3. 上海税务口径下，开通后可在 72 小时内下载数据\n4. 分部门申报的企业，数据下载存在限制\n5. WEB 端和扣缴端都支持人员信息、专项附加扣除信息、扣缴申报、查询统计等模块\n\n这意味着：\n\n1. `precheck_payroll_filing` 不能只假设数据永远齐全\n2. 要把“系统数据恢复能力”和“历史申报数据可追溯性”纳入风险提示\n3. "},{"path":"references/compensation-workflows.md","content":"# 中国 HR 薪酬高频工作流\n\n这个 skill 当前只先做一个场景，但背后的工作流语境来自中国 HR 常见的薪酬操作链路。\n\n## 常见月度链路\n\n1. 人员异动确认\n2. 考勤、绩效、补发补扣等数据收集\n3. 算薪\n4. 差异复核\n5. 个税申报\n6. 社保申报\n7. 公积金汇缴\n8. 发薪与留痕\n\n## 当前最适合 AI 的两个切入点\n\n### 1. 薪酬判断\n\n包括：\n\n1. 薪酬 band 校验\n2. 市场调研摘要\n3. 定薪建议\n\n这类工作适合做“高阶判断型 Skill”，因为它很像资深 HR 脑子里的隐性判断。\n\n### 2. 申报前检查\n\n第一版不做完整算薪，而做：\n\n1. `band / 调研 / 定薪建议`\n2. `申报前检查`\n\n原因：\n\n1. 一个负责专业感与判断感\n2. 一个负责落地感与风险感\n3. 两者合在一起，才更像真实中国薪酬模块\n\n## 当前最应该优先识别的问题\n\n1. 人员漏报\n2. 离职人员仍在申报名单\n3. 申报主体错误\n4. 缴纳地错误\n5. 社保、公积金基数异常\n6. 专项附加扣除信息缺失或异常\n7. 银行卡或身份证号缺失"},{"path":"references/dynamic-market-data-architecture.md","content":"# 薪酬市场动态数据架构\n\n更新时间：2026-05-19\n\n这份文件回答 3 个问题：\n\n1. 薪酬市场调研数据从哪里来\n2. 哪些数据可以动态拿，哪些不能\n3. skill 应该如何区分“市场信号”和“正式定薪依据”\n\n## 一、核心原则\n\n薪酬 skill 不能把所有数据都当成同一种证据。\n\n至少要区分 4 层：\n\n1. `official_policy`\n 官方动态资料，例如国家统计局、税务局、公积金中心、地方人社口径\n2. `public_market_signal`\n 公网职位薪资、招聘平台公开区间、景气和招聘热度\n3. `paid_survey_data`\n 企业采购的薪酬调研结果，例如 Mercer、智联企业薪酬调研等\n4. `internal_company_data`\n 企业自己的 band、内部同岗参考、预算、历史 offer、接受率\n\n## 二、每一层能做什么\n\n### `official_policy`\n\n能支持：\n\n1. 合规边界\n2. 城市年度口径\n3. 社保、公积金、个税相关约束\n4. 宏观工资趋势\n\n不能直接支持：\n\n1. 某一岗位的精准定薪\n2. 某一级别的 P50/P75 报价\n\n### `public_market_signal`\n\n能支持：\n\n1. 当前市场招聘热度\n2. 公开薪资区间趋势\n3. 城市、行业、岗位的招聘侧价格信号\n\n不能直接支持：\n\n1. 最终成交薪资\n2. 企业内部公平\n3. 可审计的正式定薪依据\n\n所以它最多只能作为：\n\n`market signal only`\n\n### `paid_survey_data`\n\n能支持：\n\n1. 分城市、分岗位、分级别的市场分位点\n2. 定薪、调薪、band 校准\n3. 对业务或老板的正式解释材料\n\n这是最接近真实薪酬 benchmark 的外部数据。\n\n### `internal_company_data`\n\n能支持：\n\n1. band 判断\n2. 内部公平判断\n3. 预算约束\n4. 历史 offer 一致性\n5. 真正的审批建议\n\n这是最终定薪最关键的一层。\n\n## 三、skill 的判断权重\n\n对于 `review_compensation_band_and_offer`，建议使用下面的判断优先级：\n\n1. `internal_company_data`\n2. `paid_survey_data`\n3. `public_market_signal`\n4. `official_policy`\n\n## 四、什么时候允许 skill 给出强结论\n\n### 可以给“正式建议”\n\n至少满足：\n\n1. 有 `band`\n2. 有 `internal_company_data`\n3. 有 `paid_survey_data` 或高质量市场分位点\n4. 有候选人当前薪资或总包口径\n5. 有预算范围\n\n### 只能给“弱建议”或“仅市场信号判断”\n\n如果出现这些情况：\n\n1. 只有公网职位薪资，没有正式调研\n2. 没有内部 band\n3. 没有内部同岗同级参考\n4. 没有预算\n5. 候选人只有期望薪资，没有当前薪资或总包口径\n\n这时 skill 必须主动说：\n\n1. 当前只能给市场信号判断\n2. 不能作为正式定薪依据\n3. 还缺哪些数据\n\n## 五、建议的输入结构\n\n建议每次定薪判断输入都显式区分来源：\n\n```text\npolicy_context\npublic_market_signal\npaid_survey_data\ninternal_company_data\ncandidate_compensation_context\n```\n\n不要把所有东西都混在一个 `market_benchmark` 里。\n\n## 六、最小可行动态方案\n\n如果现在就要做一个“动态版薪酬 skill”，最实际的路线是：\n\n1. 官方动态口径：由 skill 内置并定期更新\n2. 公网市场信号：允许用户补充或人工抓取摘要\n3. 正式调研数据：由用户上传最新报告或 Excel\n4. 企业内部数据：由用户上传 band、预算、内部参考\n\n也就是说：\n\n`动态` 不等于 `全靠 skill 自己上网抓`\n\n而是：\n\n`skill 能持续消费会变化的数据，并且知道每种数据能撑起多强的判断`"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"做定薪判断，也先把申报前风险挑出来 / Price offers and catch filing risks Skill: Compensation Repo Owner: ashley-aihr Summary: 做定薪判断，也先把申报前风险挑出来 / Price offers and catch filing risks Tags: china:0.2.0, compensation:0.2.0, hr:0.2.0, latest:0.5.0, payroll:0.2.0 Version history: v0.5.0 | 2026-05-18T20:34:48.346Z | auto **Summary:** Introduces dynamic market data handling, clearer output protocols, and improved decision logic for compensation and payroll checks. - 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