#!/bin/sh
set -eu

if [ "$#" -ne 2 ] && [ "$#" -ne 3 ]; then
    echo "usage: $0 FULL_MODEL_PROFILE_JSON OPERATOR_PROFILE_JSON [OUTPUT_JSON]" >&2
    exit 2
fi

full_model=$1
operator=$2
output=${3:-}

analyze()
{
    jq -n --slurpfile full "$full_model" --slurpfile operator "$operator" '
      $full[0] as $f | $operator[0] as $o |
      if ($f.schema_version != 1 or $o.schema_version != 1 or
          $f.engine != "gem-native-c-metal" or $o.engine != $f.engine or
          $f.workload != "authentic-one-token-decode-stage-profile" or
          $o.workload != "synthetic-exact-shape-decode-attention-stage-profile" or
          $o.shape != "31b-full" or $f.position != $o.tokens or
          $o.live_tokens != $o.tokens or $f.rows != 1 or $f.layers != 60 or
          $f.repetitions < 3 or $o.repetitions < 3 or
          ($f.gpu_seconds_samples | length) < 3 or
          ($o.stages.value.samples_seconds | length) < 3 or
          $f.mean_gpu_seconds <= 0 or $f.mean_sampled_gpu_seconds <= 0 or
          $f.sample_coverage < 0.95 or
          $f.layers_by_stage.kv_attention.mean_seconds <= 0 or
          $o.mean_gpu_seconds <= 0 or $o.stages.value.mean_seconds <= 0)
      then error("decode residual inputs are not comparable") else
        10 as $full_attention_layers |
        ($o.mean_gpu_seconds * $full_attention_layers) as $global_attention_seconds |
        ($o.stages.value.mean_seconds * $full_attention_layers) as $global_value_seconds |
        (100 * $global_value_seconds / $f.mean_gpu_seconds) as $value_ceiling_pct |
        (100 * $global_attention_seconds /
          $f.layers_by_stage.kv_attention.mean_seconds) as $kv_attribution_pct |
        (3 / $value_ceiling_pct * 100) as $required_value_gain_pct |
        ($f.gpu_seconds_samples |
          map((. - $f.mean_gpu_seconds) | if . < 0 then -. else . end) |
          max * 100 / $f.mean_gpu_seconds) as $max_model_deviation_pct |
        {
          schema_version: 1,
          engine: $f.engine,
          workload: "decode-value-residual-screen",
          model: $f.model,
          position: $f.position,
          model_attention_kernel: ($f.attention_kernel // "production-default"),
          operator_value_kernel: ($o.value_kernel // "unspecified"),
          full_attention_layers: $full_attention_layers,
          evidence: {
            model_mean_gpu_seconds: $f.mean_gpu_seconds,
            model_sample_coverage: $f.sample_coverage,
            model_max_sample_deviation_pct: $max_model_deviation_pct,
            kv_attention_mean_seconds: $f.layers_by_stage.kv_attention.mean_seconds,
            per_layer_operator_mean_seconds: $o.mean_gpu_seconds,
            per_layer_value_mean_seconds: $o.stages.value.mean_seconds,
            attributed_global_attention_seconds: $global_attention_seconds,
            attributed_global_value_seconds: $global_value_seconds,
            attributed_global_attention_fraction_of_kv_pct: $kv_attribution_pct
          },
          residual: {
            theoretical_whole_token_value_ceiling_pct: $value_ceiling_pct,
            value_gain_required_for_3pct_whole_token_pct: $required_value_gain_pct,
            projected_whole_token_gain_at_25pct_value_gain_pct: ($value_ceiling_pct * 0.25),
            projected_whole_token_gain_at_50pct_value_gain_pct: ($value_ceiling_pct * 0.50)
          },
          screening: {
            admissible: ($value_ceiling_pct >= 3 and $kv_attribution_pct <= 100),
            promotion_eligible: false,
            reason: (if $value_ceiling_pct < 3 then
              "theoretical P*V ceiling is below the whole-token promotion floor"
            elif $kv_attribution_pct > 100 then
              "synthetic attention attribution exceeds authentic KV-attention time"
            else
              "residual ceiling admits one-axis operator screening; authentic correctness and model/server gates remain required"
            end)
          }
        }
      end'
}

if [ -n "$output" ]; then
    analyze > "$output"
else
    analyze
fi