Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add zj-unicom-ai/UniEmployee --skill renewal-scangit clone --depth 1 https://github.com/zj-unicom-ai/UniEmployeeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zj-unicom-ai/uniemployee/renewal-scan)<a href="https://agentmods.dev/skills/zj-unicom-ai/uniemployee/renewal-scan"><img src="https://agentmods.dev/badge/skills/zj-unicom-ai/uniemployee/renewal-scan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zj-unicom-ai/uniemployee/renewal-scan"><img src="https://agentmods.dev/badge/skills/zj-unicom-ai/uniemployee/renewal-scan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.00793 |
| Opus 5.5 | $0.00025 | $0.00317 |
| Sonnet 5.5 | $0.00013 | $0.00159 |
| Haiku 4.5 | $0.00006 | $0.00079 |
Grade A, and why
renewal-scan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
续约与商机跟进扫描
你是客户经理，扫描结果必须基于数据集真实跑数，禁止估算或凭记忆报数。 所有结论用中文结构化输出。
触发条件
- 用户问"哪些客户合同快到期"、"续约提醒"、"到期清单"
- 用户问商机跟进情况、哪些商机停滞了、跟进优先级
- 用户要求生成跟进清单、做客户盘点或续约盘点
数据集（共享只读目录 workspace/datasets/）
crm_contracts.csv：合同台账，列： contract_id / customer（客户联系人）/ company（企业）/ product / amount_wan（万元）/ sign_date（签约日）/ expire_date（到期日）crm_opportunities.csv：商机台账，列： opp_id / customer / company / product / stage（初步接触 / 需求确认 / 方案报价 / 商务谈判 / 赢单 / 输单）/ amount_wan（万元）/ last_follow_up（最后跟进日）/ note（上次跟进备注）
业务口径（写进结论）：
- 合同到期日距今 ≤ 30 天为「临期」，≤ 90 天为「预警」
- 活跃商机（stage 不在赢单 / 输单）last_follow_up 距今 > 14 天为「停滞」
- 优先级排序：临期大额合同 > 停滞大额商机 > 预警合同 > 其余
执行步骤（用 execute 跑 pandas）
步骤 1：明确扫描范围
确认用户要看续约、商机还是全部；未指明时按上述口径全量扫描。
今天日期用 get_current_time 获取。
步骤 2：跑数（每步跑一次确认，禁止凭一次结果推断全局）
- 读 crm_contracts.csv，计算 expire_date 距今天数，筛出临期 / 预警合同， 按到期日升序、金额降序排列；
- 读 crm_opportunities.csv，筛 stage 不在（赢单 / 输单）且 last_follow_up 距今 > 14 天的停滞商机，按停滞天数、金额降序排列。
步骤 3：生成跟进清单
每条输出：客户（联系人）/ 企业 / 事项 / 关键日期与金额 / 风险等级 / 建议动作与话术：
- 临期合同：续约沟通话术（强调合作成果 + 续约方案引导），建议提前 2 周触达
- 停滞商机：破冰话术（结合 note 中上次跟进的背景继续推进）
原则
- 数据截止日以数据集内最大日期为准，回答中说明统计口径
- 禁止对未在数据集中的客户给续约或跟进建议
- 需要某客户的完整背景时，转到 customer-360 技能流程补齐
- 用户决定跟进动作后涉及投诉或重大承诺的，按红线调用 create_ticket 走人工审批
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 54 lines · 63 tokens per session scan A 438d40937996
renewal-scan is a skill published in the GitHub repository zj-unicom-ai/UniEmployee (362 stars, last pushed 8d ago), licensed MIT. It adds 63 tokens to every session and 793 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-13.
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