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-inquiry-response-reviewgit 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-inquiry-response-review)<a href="https://agentmods.dev/skills/qiushen-first/cn-investment-banking-skills/cn-ib-inquiry-response-review"><img src="https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-inquiry-response-review/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-inquiry-response-review"><img src="https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-inquiry-response-review.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 | $0.00118 | $0.01065 |
| Opus 5 | $0.00059 | $0.00532 |
| Sonnet 5 | $0.00024 | $0.00213 |
| Haiku 4.5 | $0.00012 | $0.00106 |
Grade A, and why
cn-ib-inquiry-response-review 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CN IB Inquiry Response Review
Turn each regulatory question into an auditable set of answer obligations, then test whether the response and intermediary work actually satisfy them.
Principles
- Review against the regulator's verbs and subquestions, not only the response headings.
- Separate the issuer's explanation from sponsor, counsel, and accountant procedures and opinions.
- A conclusion without evidence is incomplete; a procedure without procedure evidence is not demonstrated.
- Track whether material response content is synchronized into the prospectus or other filing.
- Compare rounds so that a new explanation does not silently contradict an earlier response.
- Mark judgment calls and likely follow-up questions explicitly.
Workflow
1. Establish scope
Confirm the inquiry round, regulator, board, filing version, response cut-off, responsible intermediaries, and documents in scope. Preserve the original question numbering and wording.
2. Decompose every question
Read references/question-decomposition.md. Split the question by:
- each operative verb such as
说明,披露,量化分析,核查, or发表明确意见; - each period, entity, product, transaction, and exception;
- each addressed party;
- each requested comparison, explanation, evidence item, and filing update.
Use one row per atomic obligation and addressee in assets/inquiry-review-template.csv. Do not combine issuer disclosure and intermediary opinion in one untestable row.
3. Test the issuer response
For each issuer item, determine whether it is answered, partial, unanswered, or genuinely not_applicable. Check:
- direct answer to the requested point;
- relevant facts, periods, units, definitions, and denominators;
- quantitative support where the question requests it;
- explanation of exceptions and adverse evidence;
- exact source or filing locator;
- consistency with prior rounds and other filing documents.
Read references/response-quality.md before classifying completeness.
What ships with it
6 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 · 116 lines · 118 tokens per session scan A af1681d38985
cn-ib-inquiry-response-review 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 118 tokens to every session and 1,065 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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