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 Qiushen-first/cn-investment-banking-skills --skill cn-ib-regulatory-case-researchgit clone --depth 1 https://github.com/Qiushen-first/cn-investment-banking-skillsWrote 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/qiushen-first/cn-investment-banking-skills/cn-ib-regulatory-case-research)<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.
<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>- NVIDIA SkillSpector pass
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 | $0.00113 | $0.00960 |
| Opus 5 | $0.00056 | $0.00480 |
| Sonnet 5 | $0.00023 | $0.00192 |
| Haiku 4.5 | $0.00011 | $0.00096 |
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.
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 — 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
- Search primary regulatory and issuer filings before media, databases, or summaries.
- Separate question similarity, fact-pattern similarity, business similarity, and procedural-stage similarity.
- Preserve the exact question, response, intermediary procedure, conclusion, source URL/file, and page.
- Do not treat a precedent as binding law or assume a past outcome predicts the current review result.
- Distinguish what the issuer stated from what the sponsor, counsel, or accountant verified.
- 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:
- exchange and CSRC filing pages;
- issuer-filed prospectuses, inquiry responses, sponsor reports, and legal/accounting opinions;
- official rules, guidance, and disciplinary decisions;
- licensed databases or structured filing repositories;
- 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.
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.
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 · 125 lines · 113 tokens per session scan A eb40dc20e1f5
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.
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