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-risk-screengit 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-risk-screen)<a href="https://agentmods.dev/skills/zhanglunet/qcc/qcc-risk-screen"><img src="https://agentmods.dev/badge/skills/zhanglunet/qcc/qcc-risk-screen/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-risk-screen"><img src="https://agentmods.dev/badge/skills/zhanglunet/qcc/qcc-risk-screen.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 | $0.00279 | $0.01487 |
| Opus 5.5 | $0.00112 | $0.00595 |
| Sonnet 5.5 | $0.00056 | $0.00297 |
| Haiku 4.5 | $0.00028 | $0.00149 |
Grade A, and why
qcc-risk-screen 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.
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
qcc-risk-screen — 全维度风险扫描
何时用
- 授信 / 担保 / 合同审批的最后一道闸
- 供应商 / 经销商准入审核
- M&A 标的红线扫描
- 投后监控(定期跑 + diff 上次结果)
- 客户 / 合作方异动告警
不用的场景
- 只是想知道有没有失信(单点查询):直接调单个 tool 即可,不需要 skill
- 个人(法代 / 高管)的司法风险 →
qcc-executive-background - 想找特定案号的判决书原文 → QCC 只给摘要,要原文走裁判文书网
调用流程
步骤 0:qcc-anchor → USCC
步骤 1:按 4 个优先级分组并行调用(配额紧张时只跑 P0)。
P0 — 直接 red flag(12 个,必跑)
| tool | 触发即高危 |
|---|---|
get_dishonest_info |
被执行人 / 失信被执行人 |
get_exit_restriction |
限制出境 |
get_high_consumption_restriction |
限制高消费 |
get_judgment_debtor_info |
被执行人 |
get_serious_violation |
严重违法失信名单 |
get_business_exception |
经营异常 |
get_bankruptcy_reorganization |
破产重整 |
get_tax_violation |
税收违法 |
get_tax_abnormal |
税务异常 |
get_tax_arrears_notice |
欠税公告 |
get_simple_cancellation_info |
简易注销中(主体可能即将消失) |
get_disciplinary_list |
联合惩戒名单 |
P1 — 在册案件 / 诉讼(7 个)
| tool | 含义 |
|---|---|
get_judicial_documents |
裁判文书摘要 |
get_case_filing_info |
在册立案 |
get_court_notice |
在册法院公告 |
get_hearing_notice |
在册未审开庭公告 |
get_pre_litigation_mediation |
诉前调解 |
get_service_notice |
送达公告 |
get_service_announcement |
送达通知 |
P2 — 财产 / 股权 / 抵质押(8 个)
| tool | 含义 |
|---|---|
get_equity_freeze |
股权冻结 |
get_equity_pledge_info |
股权出质 |
get_stock_pledge_info |
股票质押 |
get_chattel_mortgage_info |
动产抵押 |
get_land_mortgage_info |
土地抵押 |
get_judicial_auction |
司法拍卖 |
get_property_asset_announcement |
财产公告 |
get_valuation_inquiry |
询价评估 |
P3 — 行政 / 清算 / 终本(7 个)
| tool | 含义 |
|---|---|
get_administrative_penalty |
行政处罚 |
get_environmental_penalty |
环保处罚 |
get_default_info |
违约 / 欠款 |
get_guarantee_info |
对外担保 |
get_liquidation_info |
清算 |
get_cancellation_record_info |
注销记录 |
get_public_exhortation |
公开催告 |
get_terminated_cases |
终结本次执行 |
优先级 cutoff(用户没指定时的默认行为)
- 默认跑 P0 + P1(19 个 tool)
- 用户说"全维度" / "深度" → 跑完整 34 个
- 用户说"快速" / "授信前 30 秒" → 只跑 P0(12 个)
输出契约
red_flags: # P0 命中
- dimension: 失信被执行人
count: 0
records: []
litigation: # P1
- dimension: 在册立案
count: 3
records: [{case_no, plaintiff, defendant, date, status}]
encumbrance: # P2
- dimension: 股权出质
count: 2
financial_admin: # P3
- dimension: 行政处罚
count: 0
risk_score_hint: # 给 Agent 用的速读
level: "low | medium | high"
reasoning: "..."
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.
- 1mo ago First seen · 122 lines · 279 tokens per session scan A 0a064f04bc01
qcc-risk-screen is a skill published in the GitHub repository zhanglunet/qcc (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 279 tokens to every session and 1,487 once invoked, about $0.0011 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 2026-08-31.
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