Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Analyze debt payoff software — avalanche vs snowball strategy engines, interest calculation accuracy, amortization schedules, payment scheduling automation, credit score impact modeling, hardship accommodation workflows, and progress visualization.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
You are an autonomous debt payoff strategy analyst. Do NOT ask the user questions. Read the actual codebase, evaluate debt management algorithms, interest calculations, payment scheduling, credit score modeling, hardship workflows, and progress visualization, then produce a comprehensive analysis.
TARGET: $ARGUMENTS
If arguments are provided, use them to focus the analysis (e.g., "avalanche strategy" or "interest calculations"). If no arguments, run the full analysis.
Step 1.1 -- Technology Stack
Scan package manifests and config files to identify: platform type (web app, mobile, API service, hybrid), backend framework, database engine, financial calculation libraries, charting/visualization libraries, notification services, payment processing integrations, credit bureau API connections, data export formats.
Step 1.2 -- Debt Data Model
Read core data structures and schemas for:
Step 1.3 -- External Integrations
Map external data sources: bank account aggregation (Plaid, Yodlee, MX), credit bureau APIs (Experian, TransUnion, Equifax), payment processors, loan servicer APIs, credit score simulators, financial literacy content providers, budgeting tool integrations.
Step 2.1 -- Avalanche Method
Verify: correct ordering by interest rate (highest first), minimum payment allocation to all debts before extra payments, extra payment targeting to highest-rate debt, rollover of freed payments when a debt is eliminated, handling of variable-rate debts (rate recalculation triggers), proper treatment of promotional 0% APR periods (switch targeting before promo expires), total interest saved calculation accuracy.
Step 2.2 -- Snowball Method
Verify: correct ordering by balance (smallest first), psychological milestone tracking (debt elimination celebrations), minimum payment allocation accuracy, rollover mechanics, handling of debts with equal balances (tiebreaker logic), total interest cost comparison vs. avalanche, estimated payoff timeline calculation.
Step 2.3 -- Hybrid and Custom Strategies
Verify: hybrid options (e.g., snowball first two debts then avalanche), user-defined priority ordering, consolidation scenario modeling (new single loan replacing multiple debts), balance transfer optimization (fee vs. interest savings), refinancing scenario comparison, lump-sum windfall allocation, bi-weekly payment strategies, round-up payment integration.
Step 2.4 -- Strategy Comparison Engine
Verify: side-by-side comparison of all strategies for the same debt portfolio, metrics compared (total interest paid, time to debt-free, number of debts eliminated per year, monthly cash flow impact), sensitivity analysis (what if extra payment changes by +/- $100), break-even analysis for consolidation and balance transfers.
Step 3.1 -- Interest Computation Methods
Verify: daily vs. monthly accrual handling, average daily balance calculation, compound interest frequency (daily, monthly, continuous), grace period handling (credit cards -- no interest if paid in full), minimum interest charges, interest rate type handling (fixed, variable, introductory/promotional), APR to daily rate conversion accuracy (APR / 365 vs. APR / 360), amortization schedule generation.
Step 3.2 -- Edge Cases
Verify: leap year handling in daily interest (365 vs. 366 days), partial month interest on new debts, interest on late fees and penalties, capitalized interest (unpaid interest added to principal -- student loans), negative amortization detection, interest rate change mid-billing-cycle, retroactive interest on expired promotional rates, compound-on-compound accuracy over long horizons.
Step 3.3 -- Amortization Accuracy
Verify: amortization table generation for each debt type, remaining balance accuracy after each payment, final payment adjustment (last payment often differs), extra payment impact on amortization recalculation, total interest over life of loan, comparison with official servicer amortization tables when available.
Step 4.1 -- Payment Calendar
Evaluate: due date tracking per debt, payment frequency options (monthly, bi-weekly, weekly), multi-debt payment coordination (stagger or batch), income-aligned scheduling (pay debts after payday), holiday and weekend adjustment logic, payment processing lead time accounting.
Step 4.2 -- Automation Features
Evaluate: automatic minimum payment scheduling, extra payment auto-allocation based on selected strategy, payment amount adjustment when a debt is eliminated, notifications before payment processing, failed payment retry logic, insufficient funds handling, payment confirmation tracking.
Step 4.3 -- Payment Flexibility
Evaluate: skip-a-payment handling (recalculates timeline and interest cost), temporary payment reduction workflows, extra payment one-time vs. recurring, payment reallocation when priorities change, mid-cycle strategy switching (avalanche to snowball), pause and resume functionality.
Step 5.1 -- Credit Utilization Tracking
Evaluate: credit utilization ratio calculation per card and aggregate, utilization projection as balances decrease, optimal utilization targets (below 30%, below 10%), impact of closing accounts after payoff on utilization, authorized user considerations.
Step 5.2 -- Score Impact Projections
Evaluate: credit score change estimates as debts are paid down, factors modeled (utilization, payment history, account age, credit mix, new inquiries), score projection methodology (FICO simulation, VantageScore, or proprietary), projection accuracy validation, timeline to target score milestones, impact of debt-free status.
Step 5.3 -- Score Model Transparency
Evaluate: whether the model explains which factors drive score changes, confidence intervals on projections, disclaimers about model limitations, comparison with actual score (if credit monitoring integrated), handling of derogatory marks (collections, charge-offs, bankruptcies).
Step 6.1 -- Income Change Handling
Evaluate: income reduction scenario modeling, job loss planning mode (minimum payments only, prioritize essentials), income increase reallocation (automatically increase extra payments), irregular income handling (freelancers, seasonal workers), household income vs. individual income support.
Step 6.2 -- Hardship Accommodation Workflows
Evaluate: deferment and forbearance modeling (paused payments, accruing interest), income-driven repayment plan integration (student loans -- IBR, PAYE, REPAYE, SAVE), hardship program eligibility detection, creditor negotiation guidance (lower rate, waive fees, settlement), debt management plan (DMP) comparison, bankruptcy impact modeling (Chapter 7 vs. 13), statute of limitations awareness for old debts.
Step 6.3 -- Emergency Fund Integration
Evaluate: whether the system balances debt payoff vs. emergency savings, recommended emergency fund targets before aggressive debt payoff, unexpected expense impact on debt timeline, emergency fund depletion recovery planning.
Step 7.1 -- Dashboard and Charts
Evaluate: total debt balance over time chart, individual debt payoff progress bars, interest paid vs. principal paid breakdown, debt-free date countdown, milestone markers (each debt eliminated, percentage milestones), comparison to original timeline (ahead or behind), monthly payment waterfall visualization.
Step 7.2 -- Motivational Features
Evaluate: debt elimination celebrations, streak tracking (consecutive on-time payments), total interest saved vs. minimum-payment-only scenario, net worth impact tracking, community or social features (anonymized progress sharing), gamification elements (badges, levels, challenges).
Step 7.3 -- Reporting and Export
Evaluate: monthly progress reports, year-end tax-relevant summaries (mortgage interest, student loan interest deduction), data export for financial advisors, printable debt payoff plan, scenario comparison reports.
Write analysis to docs/debt-payoff-analysis.md (create docs/ if needed).
After producing output, validate data quality and completeness:
IF VALIDATION FAILS:
IF STILL INCOMPLETE after 2 iterations:
docs/debt-payoff-analysis.mdCritical findings:
Top recommendations:
NEXT STEPS:
/spending-behavior to analyze the budgeting and spending tracking that feeds debt payoff capacity."/retirement-optimizer to evaluate the debt payoff vs. retirement savings trade-off modeling."/security-review to audit access controls on financial account data."DO NOT:
After producing output, record execution metadata for the /evolve pipeline.
Check if a project memory directory exists:
~/.claude/projects/skill-telemetry.md in that memory directoryEntry format:
### /debt-payoff — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}
Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..
日本語の概要は準備中です。原文の説明を表示しています。
Create and manage Architecture Decision Records using the Michael Nygard format. Triggers: you need to document architecture decisions, record technical choices, explain why a technology was chosen.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes affordable housing management software for unit allocation algorithms, waitlist management, income verification workflows, Fair Housing compliance, LIHTC and Section 8 program tracking, inspection scheduling, and tenant reporting..
日本語の概要は準備中です。原文の説明を表示しています。
Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
日本語の概要は準備中です。原文の説明を表示しています。