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Analyze Token Waste

Use check to analyze a payload and see how much each strategy would save — without modifying the input.

CLI

Bash
# From stdin
echo '{"name": "Alice", "age": 30, "notes": null}' | axm-smelt check

# From a file
axm-smelt check --file data.json

Output:

Text Only
Format: json
Tokens: 18
Strategies applied: none
Strategy estimates:
  minify: 22.2%
  drop_nulls: 16.7%
  strip_quotes: 5.6%

Only strategies with positive savings are shown — strategies that would produce no savings or increase tokens are automatically filtered out.

Isolated estimates vs. real cumulative gain

The per-strategy strategy_estimates are measured in isolation, each against the unmodified input. They are independent and non-additive: summing them overstates the achievable reduction, because strategies overlap (for example minify already removes whitespace that collapse_whitespace would also target).

For the figure you can actually expect, read report.savings_pct. It is the real cumulative gain obtained by chaining the default strategy set (the safe preset — exactly what smelt(text) applies with no explicit strategies), so check(text).savings_pct == smelt(text).savings_pct. Already-minified input yields savings_pct == 0.

Python API

Python
from axm_smelt import check

report = check(data)

print(f"Format: {report.format.value}")
print(f"Tokens: {report.original_tokens}")

for strat, pct in report.strategy_estimates.items():
    if pct > 0:
        print(f"  {strat}: {pct:.1f}%")

Difference from smelt

check smelt
Modifies input No Yes
Returns compacted Input unchanged Compacted text
strategy_estimates Populated (isolated, non-additive) Empty
savings_pct Real cumulative gain (default strategy set) Real cumulative gain
strategies_applied Always [] Strategies that changed the output

Use check to decide which preset or strategies to use, then call smelt to apply them.