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CVP（Cost-Volume-Profit）分析・損益分岐点分析スキル。固定費・変動費の構造分析、 限界利益率の算出、損益分岐点売上高/数量の計算、安全余裕率の評価、 目標利益達成に必要な売上高のシミュレーションを行う。多品目分析にも対応。 Use when: 損益分岐点を知りたいとき、新規事業や価格変更の採算シミュレーション、 固定費削減・変動費率改善の効果試算、What-if分析に使用。 Triggers: "損益分岐点", "CVP", "break-even", "限界利益", "contribution margin", "安全余裕率", "margin of safety", "固変分解", "変動費率"
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応募プロセス全体のためのスペシャリスト。求人情報の分析、プロフィール（LinkedIn/CV）の最適化、テーラーメイドのカバーレターの生成を行います。SQLiteデータベースとフォルダ構造からASCII履歴書を生成します。cv_generator.py はスタンドアロンで移植されており、BACHランタイムは不要です。
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Exploit the noPac vulnerability chain (CVE-2021-42278 sAMAccountName spoofing and CVE-2021-42287 KDC PAC confusion) to escalate from standard domain user to Domain Admin in Active Directory environments.
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将经历和技能整理成A4单页的简洁英文简历，适合打印或导出PDF。采用沉稳配色，并可按需使用双栏布局，清晰展示工作经历、项目与量化成果。
Estimate RNA velocity, the modeled direction of gene expression change, from single-cell spliced and unspliced counts. Fit models, inspect gene-level plots, visualize trajectories, and explore relative timing and associated genes while checking model limitations.
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Analyze investment returns and portfolio risk using loss thresholds, average losses beyond those thresholds, and peak-to-trough declines. Combine simulated price paths with historical and hypothetical market shocks to produce a risk report and control recommendations.
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Retrieve price and trading volume data for US, Hong Kong, and Canadian stocks, ETFs, and indices through Yahoo Finance. Also gather company profiles, financial statements, dividends, and ownership data for market research and historical strategy testing.
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Build machine-learning trading signals from price and volume data. The workflow checks inputs, creates predictive features, and repeatedly trains on available historical data to produce bounded signals indicating predicted direction and strength.
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Assess whether a container can escape its isolation and reach the host during an authorized security test. Review privileges, shared mounts, Docker socket exposure, and runC vulnerabilities, then document demonstrated impact and remediation.
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Review dependency manifests and lockfiles to find outdated packages and known security vulnerabilities. Group proposed updates by version change, report current and suggested versions, and identify updates that need human review.
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Turn penetration test and red team results into reports for executives and technical teams. Structure findings, explain severity scores and business impact, organize evidence, and document remediation steps and retest plans.
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Investigate how a limited Linux account could gain root, the system administrator's privileges. The skill guides checks of permissions, scheduled tasks, services, and known vulnerabilities, while outlining evidence defenders can monitor during authorized security assessments.
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Evaluate older Wi-Fi clients and embedded devices for KRACK and FragAttacks vulnerabilities. Covers test suites, likely patch status, practical impact, and reporting findings by device, firmware version, and vulnerability identifier.
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Evaluate security findings before writing a bug bounty report. Check reproducibility, scope, practical impact, duplicates, and behavior across user sessions, then use submission checklists and CVSS 3.1 guidance to prepare evidence and assess severity.
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Turn validated security findings into clear bug bounty reports for HackerOne, Bugcrowd, Intigriti, or Immunefi. Provides templates, reproducible evidence structure, severity scoring guidance, and submission checks focused on demonstrated impact.
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CVE validation domain card. Use after CVE lookup has produced applicable or candidate CVEs and red-team mode needs scoped evidence to decide whether to continue, pivot, or report.
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Audit a Python project's installed dependencies for known CVEs by wrapping pip-audit (PyPA's official vulnerability auditor) and emitting findings in the canonical penetration-tester schema. Detects vulnerable direct AND transitive packages, normalizes pip-audit's severity output via OSV severity bands, falls back to pip list --outdated when pip-audit isn't installed, and supports requirements.txt, pyproject.toml (PEP 621), Pipfile.lock, and poetry.lock as input sources. Use when: pre-merge gate on a Python project, post-incident sweep after a PyPI compromise (e.g. ctx, request-toolbelt typosquats, ultralytics 8.3.42 compromise), SOC2 evidence collection, or inheriting an unfamiliar Python codebase. Threshold: any HIGH or CRITICAL CVE in the resolved dependency tree. MODERATE / LOW reported informationally. Trigger with: "audit python deps", "pip vulnerability scan", "check pypi packages for CVEs", "pip-audit run".
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Audit a Node.js project's installed npm dependency tree for known CVEs by wrapping the npm audit JSON output and emitting findings in the canonical penetration-tester schema. Detects direct AND transitive vulnerabilities, normalizes npm's severity scale (info/low/moderate/ high/critical) to the shared Severity enum, and parses both v1 and v2 audit output formats so the skill works against npm 6 and npm 7+ lockfiles. Use when: pre-merge gate on a Node project, post-incident sweep after a transitive package compromise (e.g. event-stream, ua-parser, node-ipc, color.js), SOC2 vendor-management evidence collection, or auditing an inherited or acquired Node codebase. Threshold: any HIGH or CRITICAL CVE in the resolved dependency tree. MODERATE / LOW reported informationally. Trigger with: "audit npm deps", "npm vulnerability scan", "check node packages for CVEs", "npm audit".
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End-to-end methodology for reproducing AND patching publicly disclosed, already-fixed vulnerabilities: sourcing the advisory and the fix commit, reading the patch diff, rebuilding a pinned offline lab, building a vulnerable-vs-patched contrast harness with proper controls, minimizing the trigger, designing and validating the fix, and writing it up as a blog post or whitepaper. Use this skill whenever the user wants to reproduce, demonstrate, understand, teach, or write about a known vulnerability or security incident: "reproduce this CVE", "build a repro for", "how did EchoLeak / Log4Shell / the postmark-mcp package actually work", "show me how this exploit worked", "write a blog post about this vulnerability", "set up a lab for CVE-XXXX", "pull the NVD/CVE/OSV details", or "make a PoC I can publish". Use it just as eagerly for the patching half: "how should this be fixed", "is this patch correct", "what would have caught this", "review this security fix", "write a regression test for this CVE", "how do I backport this", or "what's the right fix for this bug class" - even when the user never says the word "reproduce". Reach for it on vague asks like "help me understand this security advisory", "I want to write about this incident", or "can we test whether we were vulnerable" when a disclosed vulnerability is in play. This skill only handles ALREADY-PATCHED, publicly disclosed issues and refuses zero-day discovery, live targets, and weaponization.
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Build safe, local, defensive reproductions of ALREADY-PATCHED, publicly disclosed security vulnerabilities (CVEs, vendor advisories, AI-agent incidents) for whitepapers, control testing, and education. Use this skill whenever the user wants to reproduce, demonstrate, or write up a known vulnerability or security incident — phrases like "reproduce this CVE", "build a repro for", "demonstrate the EchoLeak/Cursor/postmark-mcp issue", "show how this exploit worked", "add a reproducibility guide", or "pull the NVD/CVE details for". It fetches advisory metadata from NVD and CVE.org, confirms the issue is fixed, and produces a vulnerable-vs-patched harness that is offline, loopback-only, and uses synthetic markers. It NEVER discovers, develops, or weaponizes new zero-days and refuses any unpatched or live-target request.
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Write a CV for someone moving into a new field, leading with transferable evidence instead of job titles that do not match. Use when asked to write a CV for a career change, I'm moving from teaching into product, how do I present my experience for a new industry, or my job titles don't fit the jobs I want. Produces a hybrid CV with a targeted summary and a relevant-skills section backed by achievements, a translation table from old-field language to new-field language, and an honest list of gaps with how to close them.
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Use when drafting, updating, or reviewing an S2-XXX security bulletin on the Struts cwiki, when preparing bulletin text ahead of a CVE request, when filling a CVE record in the ASF CVE tool (cveprocess.apache.org / Vulnogram), when deciding when to publish, when publishing a bulletin and announcing it to the ASF lists, when wrapping up after the advisory mails, or when deciding how much detail about a fixed vulnerability is safe to publish.
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Complete security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.
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Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
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