bankruptcy-monitor-qcc

bankruptcy-monitor-qcc is a skill for Claude Code, Codex from ThomasMoreAI/legal-skills-open. It costs 496 tokens per session (10,083 once invoked), scanned A, original, Apache-2.0.

A Chinese-language monitoring skill for warning about company bankruptcy and restructuring risks through Qichacha data. Qichacha is a Chinese business-information service; bankruptcy restructuring is a legal process for trying to reorganize a company's debts and operations.

In plain words
What is it for?
Use it to monitor important customers, debtors, or guarantors, track bankruptcy or liquidation proceedings, and identify points when creditors may need to act.
Why use it?
It combines historical records, information about key company personnel, and current legal signals to track risk before and during bankruptcy-related proceedings. The description says it covers warning signs such as enforcement actions, frozen shares, and repeated dishonest-debtor records.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is **使用约定**:本表列出 SKILL 内业务简写与企查查 MCP 工具的精确映射。AI 执行本 SKILL 时遇到下表"业务简写"列的词汇,**必须调用对应"MCP 工具"列**,禁止使用 web search 或自由文本推测替代。完整规范见 [QCC-MCP-TERMINOLOGY.md](../../QCC-MC.

Good fit Use it to monitor important customers, debtors, or guarantors, track bankruptcy or liquidation proceedings, and identify points when creditors may need to act.

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Install

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.

Clone the repo
git clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-open
agentmods
npx agentmods add skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for bankruptcy-monitor-qcc

README.md
[![agentmods](https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc/github.svg)](https://agentmods.dev/skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc)
Your own site
<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc/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.

agentmods 80×15 button for bankruptcy-monitor-qcc

Your own site · 80×15
<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/bankruptcy-monitor-qcc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 496 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 10,083 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00496 $0.10083
Opus 5.5 $0.00198 $0.04033
Sonnet 5.5 $0.00099 $0.02017
Haiku 4.5 $0.00050 $0.01008

Measured 23d ago against content hash d21d56d4af24, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

bankruptcy-monitor-qcc 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 23d 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.

cn/bankruptcy/skills/bankruptcy-monitor-qcc/SKILL.md · 386 lines

How it starts

The opening of the file, as written. The whole thing — 386 lines — stays where its author put it; the contents beside it link to each section on GitHub.

MCP Resource 条件读取(跨客户端兼容)

  1. 每个新会话首次执行本 SKILL 时,如客户端支持 MCP Resources,先执行资源发现并读取 qcc://skills/index、qcc://terminology/core、qcc://policy/data-discipline、qcc://policy/entity-anchoring 与 qcc://skill/bankruptcy-monitor/tool-binding。
  2. 同一会话已成功读取且 checksum 未变化时无需重复读取 Tool Binding;新会话不得沿用上一会话的读取状态。
  3. 生成最终报告前重新读取 qcc://skill/bankruptcy-monitor/report-template,并把它作为严格填空骨架;多轮会话后也必须在生成前重读。
  4. Resource 不会因连接 MCP 自动注入;AI 必须主动发现并精确读取。读取失败、客户端不支持或 URI 不可用时,不得阻断任务,继续使用 A 层与本 SKILL 内联规则。
  5. Resource 只提供稳定知识与模板,不替代 tools/list 的实时权限、Description 和 Input Schema,也不保证客户端多轮后必然遵循。

🔍 风险维度扫描 · 先扫后钻(统一规范 · 2026-06-08 · 对齐 A 层铁律 5-A)

本 SKILL 凡涉及“一次性排查 ≥ 2 个企业风险维度”(司法风险 / 失信 / 被执行 / 限高 / 经营异常 / 行政处罚 / 破产 / 担保 / 税务 等 qcc-risk 维度),一律按“先扫后钻”执行,禁止逐个原子风险工具散弹枪式调用(慢 / 贵 / 多为无效调用):

  1. 第 1 步 · 分诊(先扫):先调 mcp__qcc-risk__get_company_risk_scan(企业风险扫描)一次返回企业自身 35 项风险维度的命中计数(脱水版:有 / 无 + 条数,不含明细)。

  2. 第 2 步 · 下钻(后钻):仅对 count > 0 的维度,调对应原子风险工具取明细(具体工具见本 SKILL 工作流 / 术语对照表)。示例:scan 显示「失信 2、被执行 1、其余 0」→ 只下钻 mcp__qcc-risk__get_dishonest_info + mcp__qcc-risk__get_judgment_debtor_info。

  3. count = 0 的维度:直接判定“无记录”,不再调用该维度原子工具。

  4. 明确单一维度问句(仅查某一项,如“有没有失信”)→ 直接调对应原子工具,无需先扫(对应 A 层铁律 5-A 路由 3)。

  5. scan 只分诊、不出明细;要明细必须下钻原子工具。风险结论只陈述“命中维度 + 计数 / 明细”客观事实,不替客户判定“能不能合作 / 可不可开户”。

  6. 先扫后钻发生在实体锚定确定唯一主体之后;简称 / 品牌名仍须先 mcp__qcc-company__get_company_by_query 锁定主体,再 scan。

  7. 可引用已上线的聚合风险扫描工具:get_company_risk_scan(企业自身)、get_executive_risk_scan(董监高个人)、get_company_related_risk_scan(企业关联)、get_executive_related_risk_scan(人关联);关联扫描遵守单层预警 · 禁自动下钻;仍不得引用任何尚未上线的工具。

  8. 【定性必须有下钻证据】 对任一风险维度给出定性判断(如“多为原告身份 / 属正常维权”“轻微合规瑕疵”“诉讼活跃度正常”等)之前,必须已下钻该维度的明细工具、拿到支撑数据;未下钻则只陈述 scan 计数并标注“(未取明细)”,禁止凭 scan 计数或印象给定性。例:scan 显示「裁判文书 77」但未下钻 mcp__qcc-risk__get_judicial_documents → 只能写“裁判文书 77 条(未取明细)”,不得写“多为原告身份、属正常维权”;如需该定性,必须先下钻 get_judicial_documents(可按 role 取原告 / 被告分布)再下结论。

📌 year 留空拿全量 · 禁逐年循环(防 year 散弹枪 · 2026-07-01):立案 / 裁判文书 / 开庭公告 / 法院公告等带 year 过滤参数的诉讼类工具,取全量时 year 一律留空——接口在 year 缺省时即一次返回全部年份;严禁为“覆盖多年”而逐年(2024、2023 … 直至成立年)循环调用同一工具(实测曾逐年一直调到 1976、单次运行 60+ 次冗余调用)。需要按年做趋势分桶时,基于“留空一次拿回的全量列表”在报告侧自行分桶;role / notice_type 等其他过滤参数同理,取全量时留空;仅当明确限定某一年 / 区间时才传 year。qcc-history / qcc-executive 的同名历史 / 个人诉讼工具同理,不逐年循环。

Read the full file on GitHub · 386 lines

Changes

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.

  1. 23d ago Changed · +186 lines · +61 tokens per session d21d56d4af24
  2. 1mo ago First seen · 200 lines · 435 tokens per session scan A a79f7740330c

Subscribe to this mod's changes

bankruptcy-monitor-qcc is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 496 tokens to every session and 10,083 once invoked, about $0.0020 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 2026-08-30.

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