Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zhanglunet/qccnpx agentmods add skills/zhanglunet/qcc/qcc-person-portfolioWrote 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/zhanglunet/qcc/qcc-person-portfolio)<a href="https://agentmods.dev/skills/zhanglunet/qcc/qcc-person-portfolio"><img src="https://agentmods.dev/badge/skills/zhanglunet/qcc/qcc-person-portfolio/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/zhanglunet/qcc/qcc-person-portfolio"><img src="https://agentmods.dev/badge/skills/zhanglunet/qcc/qcc-person-portfolio.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 | $0.00263 | $0.01661 |
| Opus 5 | $0.00131 | $0.00830 |
| Sonnet 5 | $0.00053 | $0.00332 |
| Haiku 4.5 | $0.00026 | $0.00166 |
Grade A, and why
qcc-person-portfolio 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
qcc-person-portfolio — 自然人对外公司清单(反查)
何时用
- 重要自然人(创始人 / 投资人 / 实控人 / 大股东)的"对外版图"摸底
- 客户 / 投后 / 上下游尽调时需要看"这个人的法人能量"
- 关键人离职 / 跳槽前的关联资产清单
- KOL / 公众人物的商业关联面排查
- 一次性导出 Excel 给业务 / 法务 / 投资团队传阅
不用的场景
- 只关心他在某 1 家公司的风险细节(失信 / 限消 / 被执行等) →
qcc-executive-background - 想看一家公司有谁是董监高 →
qcc-basic-profile里的get_key_personnel - 想要他全网穿透到没列名的代持 / 信托 → QCC 不到,需要外部数据源
调用流程
[人名输入]
↓
[Step 1] qcc-company:get_company_by_query
↓ 查"已知关联公司"或品牌名(必要时让用户给 anchor)
[USCC anchor] ← 避免同名误锁
↓
[Step 2] 并行调 qcc-executive 6 个 tool, 都用 (anchor_uscc, person_name) 入参:
- get_executive_positions ← 当前董监高任职
- get_executive_historical_positions ← 历史董监高任职
- get_executive_legal_rep_roles ← 当前法定代表人
- get_executive_historical_legal_rep_roles ← 历史法定代表人
- get_executive_controlled_companies ← 控制企业(可能截断 100 条)
- get_executive_related_companies ← 全部关联企业
↓
[Step 3] Python 脚本合并去重 → 8 sheet xlsx
↓
[Step 4] 输出到指定路径
anchor 怎么找
一句话:用这个人公开任过法代或董事的任何一家公司就行。anchor 的唯一作用是消除同名歧义。
实操:
- 谷歌 / 百科 / 招股书 / 财报里搜这个人最有名的关联公司(创始公司 / 上市公司 / 基金主体均可)
- 先
qcc-company:get_company_by_query模糊查那家公司 - 在返回的候选列表里挑"法定代表人 = 目标人物"的那一条,取 USCC
示例:雷军 → 用 "小米" 模糊查 → 候选里"小米科技有限责任公司" 法代是雷军 → USCC 91110108551385082Q 即可
怎么跑
# 前置:配好 QCC_API_KEY(参考仓库根 README "0. 配 API Key")
cd qcc/python && source .venv/bin/activate
pip install -e ".[skills]" # 装 openpyxl
# 模式 A:已知 anchor USCC(最快)
python ../skills/qcc-person-portfolio/run.py \
--person "雷军" \
--anchor 91110108551385082Q \
--out ./雷军_companies.xlsx
# 模式 B:让脚本自动 anchor(用公司名)
python ../skills/qcc-person-portfolio/run.py \
--person "雷军" \
--anchor-by-name "小米科技"
跑完打开 xlsx,8 个 sheet:
- 说明 — 元数据 + sheet 索引 + 截断提示
- 汇总(去重) — 按公司名称去重的主表
- 当前董监高任职 / 历史董监高任职 / 当前法定代表人 / 历史法定代表人 / 控制企业 / 关联企业 — 各源原始数据
输出契约
xlsx 主表(汇总(去重))字段:
| 列 | 说明 |
|---|---|
| 企业名称 | 唯一键(去重维度) |
| 出现的来源 | 该公司在哪几个 sheet 命中(如 "当前董监高任职 / 控制企业") |
| 职位 / 角色 汇总 | 跨 sheet 合并的角色集合 |
| 持股比例 / 状态 / 地区 / 行业 / 成立日期 / 注册资本 | 取最先非空的那次 |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 108 lines · 263 tokens per session scan A 191ddd08c356
qcc-person-portfolio is a skill published in the GitHub repository zhanglunet/qcc (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 263 tokens to every session and 1,661 once invoked, about $0.0013 per session on Opus 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 2026-08-31.
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