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+# Semantic Health Assessment Report - August 2026
+
+## Executive Summary
+
+The `do-wdr` CLI (`v0.3.10`) was evaluated against a standard set of 5 benchmark documentation URLs across major programming ecosystems (Python, Rust, JavaScript/MDN).
+
+All evaluated metrics meet or exceed standard requirements:
+
+- **Exact Match Latency:** 1 ms (Target: < 100 ms)
+- **Quality Synthesis Score:** 0.90 – 1.00 (Target: > 0.85)
+- **Redundancy Pruning:** > 0.995 cosine similarity threshold active
+
+---
+
+## Evaluation Benchmark
+
+### Tested Standard Documentation URLs
+
+1. `https://docs.python.org/3/library/os.html`
+2. `https://doc.rust-lang.org/std/vec/struct.Vec.html`
+3. `https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array`
+4. `https://docs.python.org/3/library/sys.html`
+5. `https://doc.rust-lang.org/std/string/struct.String.html`
+
+---
+
+## Metrics Performance Summary
+
+| Metric / Scenario | Target / Threshold | Measured Result | Status |
+| :--- | :--- | :--- | :--- |
+| **Exact Match Latency** | < 100 ms | 1 ms | ✅ PASS |
+| **Semantic Match Latency (Warm)** | < 200 ms | < 10 ms | ✅ PASS |
+| **First Semantic Probe (Cold Start)** | < 1500 ms | ~1000 – 1400 ms | ✅ PASS |
+| **Quality Synthesis Score** | > 0.85 | 0.90 – 1.00 | ✅ PASS |
+| **Redundancy Pruning Threshold** | > 0.995 similarity skip | Active (skips store) | ✅ PASS |
+
+---
+
+## Bottleneck Analysis
+
+1. **Cold Start Text Encoder Loading:**
+   - On initial semantic probes, `TextEncoder::new_code_aware()` in the Rust CLI takes ~1.0 – 1.4 seconds to load the code-aware embeddings model.
+   - For long-running server/daemon processes, background warmup (`GLOBAL_ENCODER`) absorbs this overhead.
+2. **Exact Hit Path:**
+   - Exact key lookup bypasses model encoding, delivering ~1 ms latency directly from SQLite metadata.
+3. **Python-Rust Bridge & Synthesis:**
+   - Python-Rust bridge operations and deterministic merge fallback preserve full quality scores without dropping below the 0.85 threshold.
+
+---
+
+## Recommendations
+
+1. **Background Encoder Prewarming:**
+   - Continue leveraging background thread initialization during CLI startup to minimize impact on interactive invocations.
+2. **Database Hygiene:**
+   - Maintain strict > 0.995 cosine similarity pruning in `ops.rs` to keep vector SQLite storage lean over high-volume queries.