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 zhanglunet/qcc --skill qcc-executive-backgroundgit clone --depth 1 https://github.com/zhanglunet/qccWrote 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-executive-background)<a href="https://agentmods.dev/skills/zhanglunet/qcc/qcc-executive-background"><img src="https://agentmods.dev/badge/skills/zhanglunet/qcc/qcc-executive-background/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-executive-background"><img src="https://agentmods.dev/badge/skills/zhanglunet/qcc/qcc-executive-background.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 | $0.00333 | $0.01578 |
| Opus 5 | $0.00167 | $0.00789 |
| Sonnet 5 | $0.00067 | $0.00316 |
| Haiku 4.5 | $0.00033 | $0.00158 |
Grade A, and why
qcc-executive-background 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 10d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
qcc-executive-background — 法代/高管个人背调
何时用
- 入职 / 用印 / 授信申请的关键人合规审查
- M&A 标的核心团队个人风险扫描
- 影子人物识别:法定代表人 vs 实际操盘人
- 关联企业图谱构建(基于个人对外投资)
不用的场景
- 公司主体的司法风险 →
qcc-risk-screen - 公司层面的对外投资 →
qcc-ownership-trace里的get_external_investments - 个人在其他公司任职 / 历史职位的"全网"穿透 → QCC 本 skill 是按"公司+人名"双锚定;要把一个人在 N 家公司的所有数据找全,需要循环调本 skill N 次(配额谨慎)
调用流程
步骤 0:qcc-anchor → USCC,且必须明确 personName(由用户提供 / 从 qcc-basic-profile.key_people 自动遍历)。
步骤 1:把目标人物 + USCC 同时传给所有 42 个 executive tool(并行)。
当前数据(20 个,默认全跑)
职务 / 关系(6 个):
get_executive_positions— 在该公司的职务get_executive_legal_rep_roles— 法代职位列表get_executive_investments— 个人对外投资get_executive_controlled_companies— 控制的企业get_executive_related_companies— 关联企业get_executive_beneficial_owner— UBO 身份(在哪些公司是 UBO)
当前司法/失信(14 个):
get_executive_admin_penalty— 行政处罚get_executive_case_filing— 立案get_executive_court_notice— 法院公告get_executive_hearing_notice— 开庭公告get_executive_dishonest— 失信被执行get_executive_equity_freeze— 股权冻结get_executive_equity_pledge— 股权出质get_executive_stock_pledge— 股票质押get_executive_exit_restriction— 限制出境get_executive_high_consumption_ban— 限制高消费get_executive_judgment_debtor— 被执行人get_executive_judicial_docs— 司法文书get_executive_pre_litigation_mediation— 诉前调解get_executive_service_notice— 送达get_executive_tax_violation— 税收违法get_executive_terminated_cases— 终结本次执行get_executive_property_reward_notice— 财产悬赏get_executive_valuation_inquiry— 询价
历史数据(22 个,仅在 depth=full 时跑)
get_executive_historical_* 系列,字段与"当前"一一对应。还有专属于历史的:
get_executive_historical_partners— 历史合伙人(P / GP)get_executive_historical_legal_rep_roles— 历史法代职位get_executive_historical_positions— 历史任职get_executive_historical_investments— 历史对外投资get_executive_historical_related_companies— 历史关联企业
输出契约
person:
name: "雷军"
anchored_company: "小米科技有限责任公司"
uscc: "91110108551385082Q"
current:
positions: [...]
legal_rep_roles: [...]
investments: {total: int, by_status: {}, sample: [...]}
controlled_companies: [...]
related_companies: [...]
ubo_in: [...]
judicial:
dishonest: {count, records}
judgment_debtor: {count, records}
high_consumption_ban: {count, records}
exit_restriction: {count, records}
...
historical: # 仅 depth=full
positions: [...]
legal_rep_roles: [...]
investments: [...]
partners: [...]
judicial: { ... }
risk_signals:
- "个人在当前 25 家公司任法代" / "近 3 年涉及 2 起被执行" / ...
What ships with it
1 file 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.
- 10d ago First seen · 116 lines · 333 tokens per session scan A 61380fbefe38
qcc-executive-background is a skill published in the GitHub repository zhanglunet/qcc (2 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 333 tokens to every session and 1,578 once invoked, about $0.0017 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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