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-filing-refresh-controlgit 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-filing-refresh-control)<a href="https://agentmods.dev/skills/qiushen-first/cn-investment-banking-skills/cn-ib-filing-refresh-control"><img src="https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-filing-refresh-control/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-filing-refresh-control"><img src="https://agentmods.dev/badge/skills/qiushen-first/cn-investment-banking-skills/cn-ib-filing-refresh-control.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 | $0.00106 | $0.01153 |
| Opus 5 | $0.00053 | $0.00576 |
| Sonnet 5 | $0.00021 | $0.00231 |
| Haiku 4.5 | $0.00011 | $0.00115 |
Grade A, and why
cn-ib-filing-refresh-control 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CN IB Filing Refresh Control
Treat a filing refresh as a controlled change program, not a search-and-replace exercise.
Principles
- Start from refresh drivers and dependencies before editing individual documents.
- Distinguish changed facts, changed periods, changed conclusions, and presentation-only edits.
- Propagate one source change to every downstream table, narrative, risk factor, opinion, and filing.
- Preserve old/new lineage and explain intentional non-updates.
- Require independent review and closure evidence for material changes.
- Scan for stale terms after editing, but treat search hits and non-hits as review leads only.
- Apply changes to existing Word filings as native tracked revisions by default.
Workflow
1. Define the refresh baseline
Record:
- old and new reporting cut-offs;
- documents and versions in scope;
- refresh drivers: new audit period, transaction change, inquiry response, rule change, corporate event, or correction;
- approved new source documents;
- freeze date, owners, reviewers, and delivery deadline.
Read references/refresh-drivers.md and build a driver-to-document impact map.
2. Build the refresh register
Use assets/refresh-register-template.csv. Create one row for each affected disclosure unit, not one row per entire document. Record old/new source, period, value, unit, change type, downstream documents, update locator, consistency review, and closure evidence.
Read references/change-taxonomy.md before classifying changes.
3. Execute in dependency order
Recommended order:
- approve new source data and definitions;
- update core financial and operating tables;
- reperform totals, ratios, changes, and CAGR;
- update narrative analysis, trends, risk factors, and conclusions;
- propagate changes to sponsor, legal, accounting, inquiry, and summary documents;
- update dates, defined terms, cross-references, contents, appendices, and signatures;
- run stale-term and cross-document checks.
What ships with it
9 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.
- agents/openai.yaml 306 B
- assets/refresh-register-template.csv 505 B
- assets/stale-terms-template.csv 174 B
- references/change-taxonomy.md 937 B
- references/closure-standard.md 729 B
- references/refresh-drivers.md 1.1 KB
- scripts/compare_docx_text.py 3.4 KB runs code
- scripts/review_refresh_register.py 5.5 KB runs code
- scripts/scan_stale_terms.py 4.4 KB runs code
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 · 119 lines · 106 tokens per session scan A 14615bdb99fd
cn-ib-filing-refresh-control 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 106 tokens to every session and 1,153 once invoked, about $0.0005 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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