Tests unitarios: 51 tests para compactor, key_data, fingerprint y costes

- tests/test_compactor.py: 24 tests (estimate_tokens, extract_facts,
  build_summary, summarize_tool_output, compact_sections)
- tests/test_key_data_extraction.py: 11 tests (extracción de tables,
  records, sections, modules, pages desde tool executions)
- tests/test_fingerprint.py: 8 tests (deduplicación MD5, sort_keys,
  nested args)
- tests/test_cost_calculation.py: 8 tests (pricing formula, custom
  pricing, rounding)
- README.md: sección Tests con instrucciones de ejecución

Todos offline, sin Docker/Redis/LLM. Ejecutar: python3 -m pytest tests/ -v

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

tests/test_cost_calculation.py

@@ -0,0 +1,71 @@
+"""Tests para el calculo de costes del orquestador.
+
+Replica la formula de coste de OrchestratorEngine._run_pipeline():
+    cost_usd = (input_tokens / 1_000_000) * cost_per_1m_input
+             + (output_tokens / 1_000_000) * cost_per_1m_output
+
+Defaults: cost_per_1m_input=2.50, cost_per_1m_output=15.00
+"""
+
+import pytest
+
+
+def calculate_cost(
+    input_tokens: int,
+    output_tokens: int,
+    cost_per_1m_input: float = 2.50,
+    cost_per_1m_output: float = 15.00,
+) -> float:
+    """Replica exacta de la formula de coste en engine.py."""
+    return (
+        (input_tokens / 1_000_000) * cost_per_1m_input
+        + (output_tokens / 1_000_000) * cost_per_1m_output
+    )
+
+
+class TestCostCalculation:
+    def test_1m_input_tokens(self):
+        cost = calculate_cost(1_000_000, 0)
+        assert cost == pytest.approx(2.50)
+
+    def test_1m_output_tokens(self):
+        cost = calculate_cost(0, 1_000_000)
+        assert cost == pytest.approx(15.00)
+
+    def test_500k_input_100k_output(self):
+        cost = calculate_cost(500_000, 100_000)
+        # (500_000 / 1_000_000) * 2.50 + (100_000 / 1_000_000) * 15.00
+        # = 1.25 + 1.50 = 2.75
+        assert cost == pytest.approx(2.75)
+
+    def test_zero_tokens(self):
+        cost = calculate_cost(0, 0)
+        assert cost == 0.0
+
+    def test_custom_pricing(self):
+        cost = calculate_cost(
+            1_000_000, 1_000_000,
+            cost_per_1m_input=3.00,
+            cost_per_1m_output=10.00,
+        )
+        assert cost == pytest.approx(13.00)
+
+    def test_small_token_count(self):
+        """Pocos tokens = coste muy bajo pero no cero."""
+        cost = calculate_cost(100, 50)
+        assert cost > 0
+        assert cost < 0.01
+
+    def test_round_to_6_decimals(self):
+        """El engine hace round(cost_usd, 6)."""
+        cost = calculate_cost(1, 1)
+        rounded = round(cost, 6)
+        # (1/1M)*2.50 + (1/1M)*15.00 = 1.75e-05
+        # round(1.75e-05, 6) = 1.7e-05 (banker's rounding: 5 rounds to even)
+        assert rounded == pytest.approx(0.000017, abs=1e-7)
+
+    def test_output_more_expensive_than_input(self):
+        """Con defaults, output es 6x mas caro que input."""
+        input_cost = calculate_cost(1_000_000, 0)
+        output_cost = calculate_cost(0, 1_000_000)
+        assert output_cost == pytest.approx(input_cost * 6.0)