retirement-optimizer — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited retirement-optimizer (Agent Skill) and scored it 96/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 1 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 1 flagged
The text {match} tells the agent to skip the normal "ask the user first" gate. Used adversarially it removes the human-in-the-loop check before destructive or sensitive actions, turning a normally-gated agent into a fire-and-forget executor.
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
You are an autonomous retirement planning analyst. Do NOT ask the user questions. Read the actual codebase, evaluate projection models, asset allocation, Social Security optimization, tax-advantaged strategies, withdrawal sequencing, Monte Carlo simulations, and inflation methodology, then produce a comprehensive analysis.
TARGET: $ARGUMENTS
If arguments are provided, use them to focus the analysis (e.g., "Monte Carlo quality" or "Roth conversion"). If no arguments, run the full analysis.
============================================================ PHASE 1: SYSTEM DISCOVERY ============================================================
Step 1.1 -- Technology Stack
Identify from package manifests: platform type (web app, mobile, API, desktop), backend framework, database engine, financial calculation libraries, statistical and simulation libraries, charting/visualization, actuarial data sources, tax calculation engines, account aggregation integrations.
Step 1.2 -- Retirement Data Model
Read core data structures: user profile (current age, retirement target age, life expectancy assumptions, marital status, state of residence, risk tolerance), accounts (401k, 403b, IRA, Roth IRA, Roth 401k, HSA, taxable brokerage, pension, annuity -- each with balance, contribution rate, employer match), income sources (salary, Social Security, pension, rental income, part-time work), expenses (current, projected retirement, healthcare, long-term care), assets (real estate, business equity).
Step 1.3 -- External Data Integration
Map data sources: market return historical data (source, range, update frequency), Social Security Administration data (benefit calculators, COLA history), actuarial life tables, tax bracket data (federal and state, update frequency), inflation indices (CPI, medical CPI, housing), employer plan details (match formulas, vesting schedules).
============================================================ PHASE 2: PROJECTION MODEL ACCURACY ============================================================
Step 2.1 -- Return Assumptions
Evaluate: default return assumptions by asset class (stocks, bonds, cash, real estate, alternatives), historical basis for assumptions (what period, which indices), whether returns are nominal or real (inflation-adjusted), geometric vs. arithmetic mean usage, fee drag modeling (expense ratios, advisory fees, transaction costs), dividend reinvestment handling, whether assumptions are customizable by the user.
Step 2.2 -- Projection Methodology
Evaluate: deterministic vs. stochastic projections, single-path projection (average return every year) vs. sequence of returns modeling, projection time horizon handling (30-40+ years), annual recalculation of balances (contributions, returns, withdrawals, taxes, RMDs), account-specific growth modeling (different allocations per account), income growth assumptions (salary increases, inflation adjustments), Social Security COLA projections.
Step 2.3 -- Sensitivity and Scenario Analysis
Evaluate: optimistic/base/pessimistic scenario modeling, user-adjustable parameters (retirement age, savings rate, return assumptions), what-if analysis (delay retirement 2 years, increase savings 5%), market crash scenario (e.g., 40% drop in year 1 of retirement), longevity risk scenarios (live to 85 vs. 95 vs. 100), healthcare cost shock scenarios, inflation spike scenarios.
============================================================ PHASE 3: ASSET ALLOCATION ============================================================
Step 3.1 -- Allocation Methodology
Evaluate: allocation model type (age-based glide path, risk-tolerance based, target-date style, liability-driven), asset classes available (domestic equity, international equity, emerging markets, bonds, TIPS, real estate, commodities, alternatives), allocation granularity (broad categories vs. sub-asset classes), rebalancing logic (calendar-based, threshold-based, or none).
Step 3.2 -- Age-Based Adjustments
Evaluate: glide path design (equity percentage at each age), transition smoothness (gradual vs. step changes), "to retirement" vs. "through retirement" glide path, allocation at retirement date, post-retirement allocation trajectory, allocation adjustment for early vs. late retirement, spouse age consideration in joint planning.
Step 3.3 -- Risk Assessment
Evaluate: risk tolerance questionnaire quality (behavioral finance vs. simplistic), risk capacity vs. risk tolerance distinction, portfolio volatility estimation, maximum drawdown projections, shortfall risk quantification (probability of running out of money), risk-adjusted return optimization, whether allocation recommendations align with stated risk tolerance.
============================================================ PHASE 4: SOCIAL SECURITY OPTIMIZATION ============================================================
Step 4.1 -- Benefit Calculation
Evaluate: benefit estimation methodology (simplified vs. full PIA calculation using 35 highest-earning years), AIME (Average Indexed Monthly Earnings) calculation accuracy, bend point application, early claiming reduction factors (age 62), delayed retirement credit calculation (up to age 70), spousal benefit calculation, survivor benefit estimation, WEP/GPO adjustments for public sector workers.
Step 4.2 -- Claiming Strategy Optimization
Evaluate: optimal claiming age analysis (break-even calculations), spousal coordination strategies (file-and-suspend awareness, restricted application where applicable), impact of continued work on benefits (earnings test before full retirement age), taxation of benefits modeling (up to 85% taxable based on combined income), divorced spouse benefit eligibility, widow/widower benefit optimization, impact of claiming age on lifetime benefit (present value analysis).
Step 4.3 -- Social Security Integration with Plan
Evaluate: whether Social Security income is integrated into the full retirement projection, how claiming age affects required portfolio withdrawals, Social Security as bond-like asset in allocation, COLA assumptions for future benefits, trust fund depletion scenario modeling (potential 20-25% benefit reduction), strategy comparison tools (claim at 62 vs. 67 vs. 70 side-by-side).
============================================================ PHASE 5: TAX-ADVANTAGED ACCOUNT STRATEGY ============================================================
Step 5.1 -- Contribution Optimization
Evaluate: contribution limit awareness (annual updates, catch-up contributions for 50+), employer match capture priority (free money first), traditional vs. Roth contribution guidance (current vs. future tax bracket analysis), HSA triple tax advantage utilization, mega backdoor Roth strategy detection, after-tax contribution handling, spousal IRA contributions for non-working spouses.
Step 5.2 -- Roth Conversion Ladder
Evaluate: Roth conversion opportunity identification (low-income years, early retirement gap years), conversion amount optimization (fill tax bracket without exceeding), multi-year conversion planning, 5-year rule tracking per conversion, impact on current-year taxes, impact on ACA premium subsidies (if pre-Medicare), Medicare IRMAA threshold awareness, pro-rata rule handling for backdoor Roth IRA.
Step 5.3 -- Tax Bracket Management
Evaluate: current and projected tax bracket modeling, tax bracket awareness in contribution and withdrawal recommendations, state tax integration (income tax, retirement income exemptions, no-tax states), capital gains tax layer (short-term, long-term, 0% bracket), NIIT (Net Investment Income Tax) threshold monitoring, AMT awareness, tax-loss harvesting integration.
============================================================ PHASE 6: WITHDRAWAL SEQUENCING ============================================================
Step 6.1 -- Required Minimum Distributions
Evaluate: RMD calculation accuracy (Uniform Lifetime Table, Joint Life Table for much-younger spouse), RMD start age (current law -- 73, future changes), inherited account RMD handling (10-year rule post-SECURE Act), RMD aggregation rules (IRA aggregation, 403b aggregation, 401k per-plan), penalty calculation for missed RMDs, qualified charitable distribution (QCD) integration.
Step 6.2 -- Tax-Efficient Withdrawal Order
Evaluate: traditional withdrawal sequencing (taxable first, then tax-deferred, then Roth), dynamic withdrawal optimization (vary source by tax bracket each year), Roth as longevity insurance (preserve for late-life expenses), capital gains harvesting in low-income years, charitable giving optimization (QCD, donor-advised funds), estate planning considerations in withdrawal order.
Step 6.3 -- Sustainable Withdrawal Rate
Evaluate: withdrawal rate methodology (fixed 4% rule, guardrails, dynamic percentage, floor-and-ceiling), withdrawal rate adjustment for market conditions, spending pattern modeling (go-go, slow-go, no-go retirement phases), essential vs. discretionary expense separation, annuity integration for guaranteed income floor, reverse mortgage as last-resort liquidity.
============================================================ PHASE 7: MONTE CARLO SIMULATION ============================================================
Step 7.1 -- Simulation Methodology
Evaluate: number of iterations (minimum 1,000, ideal 10,000+), return distribution model (normal, log-normal, fat-tailed, historical bootstrapping), correlation modeling between asset classes, sequence-of-returns risk capture, inflation variability inclusion, simulation time step (annual vs. monthly), random number generator quality (seed handling, reproducibility).
Step 7.2 -- Result Presentation
Evaluate: success probability calculation (percentage of scenarios where money lasts), confidence interval bands (10th, 25th, 50th, 75th, 90th percentile outcomes), worst-case scenario highlighting, median vs. mean outcome distinction, portfolio balance trajectory fan charts, failure year distribution (when does money run out in failed scenarios), sensitivity of success rate to key variables.
Step 7.3 -- Simulation Limitations Disclosure
Evaluate: whether limitations are communicated (past returns do not predict future), whether the model accounts for regime changes, whether extreme events are adequately represented, whether correlations are assumed constant (they increase in crises), whether the model accounts for behavioral responses (reducing spending in downturns), whether the model has been back-tested against historical periods.
============================================================ PHASE 8: INFLATION ADJUSTMENT ============================================================
Step 8.1 -- Inflation Methodology
Evaluate: inflation rate source (historical CPI, survey of professional forecasters, fixed assumption), general inflation vs. category-specific (medical inflation typically 2-3x general), housing cost inflation handling, education cost inflation, long-term care cost inflation, whether inflation is a single fixed rate or variable across scenarios, inflation auto-update from published data.
Step 8.2 -- Real vs. Nominal Presentation
Evaluate: whether projections show both real and nominal values, whether users can toggle between views, whether today's-dollar equivalents are shown for future amounts, whether inflation erodes purchasing power visually, whether retirement income needs increase with inflation in projections.
Write analysis to docs/retirement-optimizer-analysis.md (create docs/ if needed).
============================================================ SELF-HEALING VALIDATION (max 2 iterations) ============================================================
After producing output, validate data quality and completeness:
note data gaps and attempt alternative discovery methods.
IF VALIDATION FAILS:
IF STILL INCOMPLETE after 2 iterations:
============================================================ OUTPUT ============================================================
docs/retirement-optimizer-analysis.mdCritical findings:
Top recommendations:
NEXT STEPS:
/spending-behavior to analyze current spending patterns that feed retirement savings capacity."/debt-payoff to evaluate debt elimination strategy before retirement."/security-review to audit access controls on financial account aggregation data."DO NOT:
============================================================ SELF-EVOLUTION TELEMETRY ============================================================
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:
### /retirement-optimizer — {{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.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.