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feat: add data-breach-blast-radius skill for pre-breach impact analysis (#1487)

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* feat: add data-breach-blast-radius skill for pre-breach impact analysis

* fix: resolve codespell false positives (ZAR currency code, SME abbreviation)

* fix: remove ZAR abbreviation to pass codespell check
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Shubham Jiyani
2026-04-27 21:26:20 -07:00
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commit 8ca38ffb9e
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docs/README.skills.md
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@@ -117,6 +117,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-skills) for guidelines on how to
| [csharp-tunit](../skills/csharp-tunit/SKILL.md) | Get best practices for TUnit unit testing, including data-driven tests | None |
| [csharp-xunit](../skills/csharp-xunit/SKILL.md) | Get best practices for XUnit unit testing, including data-driven tests | None |
| [daily-prep](../skills/daily-prep/SKILL.md) | Prepare for tomorrow's meetings and tasks. Pulls calendar from Outlook via WorkIQ, cross-references open tasks and workspace context, classifies meetings, detects conflicts and day-fit issues, finds learning and deep-work slots, and generates a structured HTML prep file with productivity recommendations. | None |
| [data-breach-blast-radius](../skills/data-breach-blast-radius/SKILL.md) | Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sourced verbatim from GDPR Art. 83, CCPA § 1798.155(a), and HIPAA 45 CFR § 160.404. Cost benchmarks from IBM Cost of a Data Breach Report (annually updated). All citations in references/SOURCES.md for verification. Use when asked: "assess breach impact", "what data could be exposed", "calculate blast radius", "data exposure analysis", "how bad would a breach be", "quantify data risk", "sensitive data inventory", "data flow security audit", "pre-breach assessment", "worst-case breach scenario", "breach readiness", "data risk report", "/data-breach-blast-radius". For any stack handling user data, health records, or financial information. Output labels law-sourced figures (exact) vs heuristic estimates (planning only). Does not replace legal counsel. | `references/SOURCES.md`<br />`references/blast-radius-calculator.md`<br />`references/data-classification.md`<br />`references/hardening-playbook.md`<br />`references/regulatory-impact.md`<br />`references/report-format.md` |
| [datanalysis-credit-risk](../skills/datanalysis-credit-risk/SKILL.md) | Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing. | `references/analysis.py`<br />`references/func.py`<br />`scripts/example.py` |
| [dataverse-python-advanced-patterns](../skills/dataverse-python-advanced-patterns/SKILL.md) | Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques. | None |
| [dataverse-python-production-code](../skills/dataverse-python-production-code/SKILL.md) | Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices | None |