ChatGPT Plugin

CostInflation

Explore and compare prices

Brand: CostInflation

Category: Data & Analytics
Primary Subcategory: Sector, Macro & Alternative Data Intelligence

Integration details

Description

Explore category price histories, compare measured quantities across supported U.S. areas, and assemble research with canonical CostInflation citations. Inspect coverage and date gaps, category-by-area matrices, exact price changes, fixed-quantity basket history and item contributions. Normalize your own USD package quotes into compatible units and compare with dated category benchmarks. Read published price bands and anonymous matched package-size changes with explicit counts and methods. Choose interactive line charts, comparison or contribution bars, matrices and sortable evidence tables; exact values, actual dates, quantity bases and missing evidence remain inspectable. The tools supply reusable evidence and calculations for your questions, with no sign-in required.

Integration type: Plugin
Verification status: Not applicable
Platform: ChatGPT
Category: Data & Analytics
Primary Subcategory: Sector, Macro & Alternative Data Intelligence
Secondary Subcategories: None listed
Brand: CostInflation
Access: No account required
First tracked: 2026-10-24
Tool count: 15
Market: US

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Primary Subcategory

Competing in ChatGPT Sector, Macro & Alternative Data Intelligence

View Category

Listed in alphabetical order

Primary Subcategory

Airside Labs Aviation ToolsComing soonGet notified

Antevo Executive BriefComing soonGet notified

AnySchoolComing soonGet notified

Ask the GridComing soonGet notified

Carbon ArcComing soonGet notified

CostInflationComing soonGet notified

Tools

15 tools agents can invoke

Compare two actual dated boundaries for selected categories and areas. Exact USD and percentage changes, zero-baseline handling and optional numeric ordering; earlier boundary dates are explicit.
get_price_changes
Calculate a basket on each calendar date with explicit quantities and units. Same-day observations by default; only an explicit bounded_as_of policy permits earlier observations. Incomplete totals are null.
get_basket_history
Attribute price changes for fixed item quantities across two dates. Complete item contributions reconcile exactly with total change; partial evidence has no complete total. Quantity changes are not mixed into this attribution.
decompose_basket_change
Price up to 30 leaf categories with exact decimal quantities and explicit units. Fetch each category's quantity basis and supported area IDs first. Use the user's physical/count unit: five pounds is quantity 5, unit pounds; 24 eggs is quantity 24, unit units; 12 ounces is quantity 12, unit ounces. display_units counts the whole displayed equivalent, not pounds or ounces. Incomplete baskets show gaps and are excluded from complete rankings.
compare_basket
Explore one category, supported area IDs, actual dates and calculated change. Omit areas to discover the panel. Dates choose latest observations on or before boundaries; at most 512 rows. The interactive view includes every observation; keep chat to requested findings, scope and citations instead of repeating its complete table.
get_price_history
Search the bounded public category catalog. Returns IDs and canonical citation URLs.
search
Inspect selected categories and areas for available dates, observed and missing days, date gaps and freshness. Does not invent coverage for missing areas.
get_coverage
Enumerate canonical category IDs, quantities, units, links and supported operations. Stable filter-aware cursor pagination; no data reads.
get_catalog
Compare user-supplied USD package prices using compatible physical/count units and a stated common quantity. Optional dated category benchmark. Supplied quotes are distinct from CostInflation observations.
compare_price_quotes
Render the view_data returned by a calculation tool as a line, bars, contribution, matrix or accessible table. Copy the typed prepared data unchanged; this presentation tool does not recalculate evidence. Line views require dated series.
render_price_view
Read exact category prices for the displayed measured quantities. Returns actual observation dates, age and missing/earlier cells for an optional as-of date.
get_price_matrix
Read consecutive-day matched-listing package quantity and unit-price change summaries. Counts expose matched, unmatched and ambiguous cohorts. Only stable identity/title/brand pairs are matched; do not label all changes shrinkflation or infer causality.
get_package_size_changes
Data-first retrieval of one resolved category's quantity basis, supported areas, dated public evidence and canonical citation URL. Prepare a final history or basket result without creating an intermediate view for each category.
fetch
Read daily p05/p25/p75/p95 bands and datapoint counts at the canonical measured quantity. Actual dates, missing areas and published weighting method are explicit. Averages of panel quantiles are not pooled percentiles; summed marginal bands are not basket percentiles.
get_price_distribution
Compute equally weighted daily min, max, nearest-rank median and current historical rank with explicit ties and gaps. These are statistics of category observations, not product-price distributions or forecasts.
get_history_statistics

FAQs

CostInflation ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

Read the methodology

How do I improve CostInflation's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

What are CostInflation alternatives on ChatGPT?

As of 2026-11-03, CostInflation competes with Airside Labs Aviation Tools, Antevo Executive Brief, AnySchool, Ask the Grid, Carbon Arc, Corporate Weather, Datalastic, EconomicsAPI and 16 more in ChatGPT Sector, Macro & Alternative Data Intelligence, ranked by public Discoverability Score.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.