cn-ib-regulatory-case-research

cn-ib-regulatory-case-research is a skill for Codex from Qiushen-first/cn-investment-banking-skills. It costs 113 tokens per session (960 once invoked), scanned A, original, Apache-2.0.

A research process for finding and comparing Chinese capital-markets regulatory precedents, meaning earlier official review questions, issuer replies, and related cases.

In plain words
What is it for?
Use it to research IPO or fundraising review questions, inquiry responses, exchange or regulator cases, comparable listings, business independence, historical ownership, and intermediary checks.
Why use it?
It separates genuinely similar cases from documents that merely share keywords and keeps the original questions, evidence, procedures, conclusions, and sources traceable.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to research IPO or fundraising review questions, inquiry responses, exchange or regulator cases, comparable listings, business independence, historical ownership, and intermediary checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research
Install

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.

Any agent
npx skills add Qiushen-first/cn-investment-banking-skills --skill cn-ib-regulatory-case-research
Clone the repo
git clone --depth 1 https://github.com/Qiushen-first/cn-investment-banking-skills

Made for: 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 cn-ib-regulatory-case-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research/github.svg)](https://agentmods.dev/skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research)
Your own site
<a href="https://agentmods.dev/skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research"><img src="https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research/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 cn-ib-regulatory-case-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research"><img src="https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 960 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 $0.00113 $0.00960
Opus 5 $0.00056 $0.00480
Sonnet 5 $0.00023 $0.00192
Haiku 4.5 $0.00011 $0.00096

Measured 12d ago against content hash eb40dc20e1f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

cn-ib-regulatory-case-research 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.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/rank_cases.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/cn-ib-regulatory-case-research/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CN IB Regulatory Case Research

Build a defensible precedent set. Do not return a list of documents that merely share keywords.

Principles

  1. Search primary regulatory and issuer filings before media, databases, or summaries.
  2. Separate question similarity, fact-pattern similarity, business similarity, and procedural-stage similarity.
  3. Preserve the exact question, response, intermediary procedure, conclusion, source URL/file, and page.
  4. Do not treat a precedent as binding law or assume a past outcome predicts the current review result.
  5. Distinguish what the issuer stated from what the sponsor, counsel, or accountant verified.
  6. Report negative and imperfect precedents when they materially inform the risk.

Workflow

1. Decompose the research question

Write an issue tree containing:

  • explicit regulatory questions;
  • implicit review concerns;
  • relevant facts and transaction structure;
  • responsible intermediary;
  • target board and review stage;
  • expected evidence and possible follow-up questions.

Do not search the full user sentence as the only query.

2. Build a search vocabulary

Read references/search-strategy.md. Create combinations of:

  • regulatory terminology;
  • business and product terminology;
  • accounting/legal synonyms;
  • issuer characteristics;
  • board and filing stage;
  • known comparable issuers.

Record every material query so the search is reproducible.

3. Search in source order

Prioritize:

  1. exchange and CSRC filing pages;
  2. issuer-filed prospectuses, inquiry responses, sponsor reports, and legal/accounting opinions;
  3. official rules, guidance, and disciplinary decisions;
  4. licensed databases or structured filing repositories;
  5. professional summaries only as discovery aids.

Use a secondary source to find a case, then return to the primary filing for evidence.

If cn-ib-source-verifier is available, use its source-connector registry to plan the access path. In particular, use 见微数据 as a case-discovery and prospectus-comparison aid, not as a substitute for the underlying exchange or CSRC document.

Read the full file on GitHub · 125 lines

Files

What ships with it

5 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.

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. 12d ago First seen · 125 lines · 113 tokens per session scan A eb40dc20e1f5

Subscribe to this mod's changes

cn-ib-regulatory-case-research is a skill published in the GitHub repository Qiushen-first/cn-investment-banking-skills (101 stars, last pushed 26d ago), licensed Apache-2.0. It adds 113 tokens to every session and 960 once invoked, about $0.0006 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 2026-08-30.

Related

Other skills, from other repositories

specification-writing

A workflow for writing complete patent specifications from patent claims and an invention disclosure. It adapts the document to a chosen jurisdiction, such as the US, Europe, or China.

wanshuiyin/Auto-claude-code-research-in-sleep · 49 tokens

regulatory-research-fallback

Fallback workflow for regulatory research when web extraction tools fail on government PDFs.

HKUDS/OpenSpace · 20 tokens

x-scorecard

OpenSSF Scorecard for assessing open source project security. Check security best practices and compliance. Dependency: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation.

x-cmd/x-cmd · 57 tokens

gesellschaftsrechtliche-satzungen-agb

Für Gesellschaftsrechtliche Satzungen AGB Abgrenzung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: gesellschaftsrechtliche-satzungen-agb.

Klotzkette/claude-fuer-deutsches-recht · 69 tokens

memstack-business-gdpr

Use this skill when the user says 'GDPR', 'data protection', 'privacy compliance', 'DPA', 'DSAR', 'data subject request', 'cookie consent', 'privacy audit', 'CCPA', or asks 'do I need GDPR for this repo'. Scans the repository to detect what personal data is collected, classifies sensitivity, determines whether GDPR…

cwinvestments/memstack · 121 tokens

nda-review

Use when the user uploads or pastes a non-disclosure agreement and asks for review, redline, risk assessment, or a recommendation on whether to sign. Identifies missing standard protections, one-sided or unusual provisions, and operational issues; produces a structured report with severity ratings and citations to…

LegalQuants/lq-ai · 79 tokens