analyzing-inflation-dynamics
Structures inflation analysis with component decomposition, expectations tracking, and Phillips curve assessment. Use when analyzing inflation, decomposing CPI/PCE, or tracking inflation expectations.
Best use case
analyzing-inflation-dynamics is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Structures inflation analysis with component decomposition, expectations tracking, and Phillips curve assessment. Use when analyzing inflation, decomposing CPI/PCE, or tracking inflation expectations.
Teams using analyzing-inflation-dynamics should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyzing-inflation-dynamics/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-inflation-dynamics Compares
| Feature / Agent | analyzing-inflation-dynamics | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Structures inflation analysis with component decomposition, expectations tracking, and Phillips curve assessment. Use when analyzing inflation, decomposing CPI/PCE, or tracking inflation expectations.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analyzing Inflation Dynamics Structures inflation analysis with component decomposition, expectations tracking, and Phillips curve assessment. ## When To Use - Decomposing CPI or PCE inflation into component drivers (food, energy, shelter, core goods, core services) - Assessing whether current inflation is demand-pull, cost-push, or expectations-driven - Tracking inflation expectations across market-based and survey-based measures - Evaluating Phillips curve dynamics (output gap vs. inflation tradeoff) - Preparing macro research notes, policy briefs, or investment committee memos on the inflation outlook - Analyzing pass-through effects from commodity prices, wages, or supply shocks ## Inputs To Gather - **Headline and core inflation series**: CPI-U, CPI-W, Core CPI (ex food & energy), PCE, Core PCE, trimmed-mean PCE, median CPI — specify frequency (monthly, quarterly, annual) and time horizon - **Component-level data**: BLS CPI component weights and contributions; shelter (OER, rent of primary residence), medical care, transportation, apparel, etc. - **Inflation expectations measures**: 5y5y breakeven, TIPS breakeven spreads, University of Michigan survey (1-year, 5-year), NY Fed Survey of Consumer Expectations, SPF median forecasts - **Labor market inputs**: unemployment rate, NAIRU estimate, unit labor costs, average hourly earnings, employment cost index (ECI) - **Supply-side indicators**: commodity price indices (WTI, Henry Hub, FAO food index), shipping rates, ISM prices-paid, supplier delivery times - **Policy context**: current federal funds rate, Fed dot plot, recent FOMC statement language, QT pace, fiscal impulse estimates ## Workflow 1. **Establish the inflation snapshot** - Report latest headline and core readings for CPI and PCE (month-over-month, 3-month annualized, year-over-year) - Compare to Fed's 2% PCE target and recent trend - Flag any divergence between CPI and PCE due to weighting or methodological differences [VERIFY methodology changes in current BLS/BEA releases] 2. **Decompose by component** - Break headline CPI into major categories: food at home, food away from home, energy (gasoline, electricity, natural gas), shelter, core goods, core services ex-shelter - Calculate contribution to headline change for each component (weight x price change) - Identify sticky vs. flexible components using Atlanta Fed sticky-price CPI - Flag any one-off or seasonal distortions (e.g., used car index volatility, airfare seasonal adjustment issues) 3. **Assess underlying inflation momentum** - Compute trimmed-mean PCE (Dallas Fed) and median CPI (Cleveland Fed) to strip outliers - Track supercore (core services ex-housing PCE) as the Fed's preferred demand-sensitive gauge - Evaluate 3-month annualized vs. 12-month to detect acceleration or deceleration trends - Determine if diffusion is broadening (share of CPI components above 2%, 3%, 5% thresholds) 4. **Analyze inflation expectations** - Compare market-based measures: 5y breakeven, 5y5y forward, inflation swap rates - Compare survey-based measures: Michigan 1y and 5y, SPF, NY Fed SCE - Assess whether expectations remain anchored near 2% or show de-anchoring risk - Note any divergence between short-term and long-term expectations (signal of transitory vs. persistent perception) 5. **Evaluate Phillips curve and macro drivers** - Estimate output gap position (CBO potential GDP vs. actual) [VERIFY latest CBO estimates] - Compare unemployment rate to NAIRU/natural rate estimates [VERIFY current Fed/CBO NAIRU range] - Track unit labor cost growth and wage-price spiral indicators (ECI vs. productivity growth) - Assess fiscal impulse: government spending contribution to aggregate demand 6. **Identify supply-side and pass-through dynamics** - Track commodity input costs and their lagged pass-through to consumer prices - Evaluate supply chain normalization (supplier delivery times, inventory-to-sales ratios) - Assess exchange rate pass-through for import prices - Note any sector-specific shocks (e.g., insurance, auto repair, housing supply constraints) 7. **Synthesize outlook and risk assessment** - State base case inflation trajectory (next 6-12 months) with key assumptions - Identify upside risks (energy shock, wage acceleration, fiscal expansion, de-anchored expectations) - Identify downside risks (demand destruction, credit tightening, commodity deflation, productivity gains) - Assess policy implications: likelihood of rate cuts/hikes, QT continuation, forward guidance shift ## Output - **Inflation Dashboard Table**: latest headline CPI, core CPI, headline PCE, core PCE, trimmed-mean PCE, supercore — each with MoM, 3M annualized, and YoY - **Component Contribution Chart Description**: ranked list of components by contribution to headline change - **Expectations Summary**: table of market-based and survey-based expectations with trend arrows - **Phillips Curve Assessment**: current positioning (unemployment vs. inflation) and directional call - **Outlook Narrative**: 2-4 paragraph synthesis with base case, risk skew, and policy implication - **Key Monitoring Points**: 3-5 specific data releases or thresholds to watch going forward ## Quality Checks - Confirm CPI and PCE readings match official BLS/BEA releases — do not rely on stale data [VERIFY release dates] - Verify component weights are current (BLS updates CPI weights annually in January) [VERIFY weight revision timing] - Ensure breakeven inflation figures are adjusted for inflation risk premium and liquidity premium where relevant - Cross-check survey expectations against the most recent release dates (Michigan is preliminary then final; SPF is quarterly) - Distinguish between seasonally adjusted and non-seasonally adjusted figures — never mix them in comparisons - Flag if analysis period spans a methodological change (e.g., OER calculation updates, geometric mean vs. arithmetic mean) - Mark any forward-looking projection as an estimate, not a forecast guarantee