test: add unit tests for tool calling test runner (#101)

- Update raw-IP forge URL to canonical forge domain in README.md
  (fixes #46)
- Update 4 broken local markdown links pointing to deleted
  BUILD-SPEC.md, PHASE1-REPORT.md, FULL-REPORT.md to
  docs/PROJECT_STATUS.md (fixes #44)

.gitignore

@@ -0,0 +1,3 @@
+build/
+*.pyc
+__pycache__/

CMakeLists.txt

@@ -0,0 +1,36 @@
+cmake_minimum_required(VERSION 3.16)
+
+project(turboquant LANGUAGES CXX)
+
+option(TURBOQUANT_BUILD_TESTS "Build standalone TurboQuant validation tests" ON)
+
+add_library(turboquant STATIC
+    llama-turbo.cpp
+)
+
+target_include_directories(turboquant PUBLIC
+    ${CMAKE_CURRENT_SOURCE_DIR}
+)
+
+target_compile_features(turboquant PUBLIC cxx_std_17)
+
+if(MSVC)
+    target_compile_options(turboquant PRIVATE /W4)
+else()
+    target_compile_options(turboquant PRIVATE -Wall -Wextra -Wpedantic)
+endif()
+
+if(TURBOQUANT_BUILD_TESTS)
+    include(CTest)
+
+    add_executable(turboquant_roundtrip_test
+        tests/roundtrip_test.cpp
+    )
+    target_link_libraries(turboquant_roundtrip_test PRIVATE turboquant)
+    target_compile_features(turboquant_roundtrip_test PRIVATE cxx_std_17)
+
+    add_test(
+        NAME turboquant_roundtrip
+        COMMAND turboquant_roundtrip_test
+    )
+endif()

README.md

@@ -13,7 +13,7 @@ Unlock 64K-128K context on qwen3.5:27b within 32GB unified memory.
 A 27B model at 128K context with TurboQuant beats a 72B at Q2 with 8K context.
 
 ## Status
-See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for current progress.
+See [issues](https://forge.alexanderwhitestone.com/Timmy_Foundation/turboquant/issues) for current progress.
 
 ## Roles
 - **Strago:** Build spec author
@@ -29,4 +29,4 @@ See [issues](http://143.198.27.163:3000/Timmy_Foundation/turboquant/issues) for
 - [rachittshah/mlx-turboquant](https://github.com/rachittshah/mlx-turboquant) — MLX fallback
 
 ## Docs
-- [BUILD-SPEC.md](BUILD-SPEC.md) — Full build specification (Strago, v2.2)
+- [Project Status](docs/PROJECT_STATUS.md) — Full project status and build specification

benchmarks/bonsai-tool-calling.md

@@ -0,0 +1,50 @@
+# Tool Calling Viability: Bonsai 1-Bit Models
+
+**Epic**: #99 (1-Bit Models + Edge)
+**Date**: TBD (run benchmarks/test_tool_calling.py to populate)
+
+## Hypothesis
+
+1-bit quantization destroys fine-grained reasoning. Tool calling (precise JSON output) may be impossible at Q1_0. But worth testing — the field is moving fast.
+
+## Models to Test
+
+| Model | Size | Quant | Source |
+|-------|------|-------|--------|
+| Bonsai-1.7B | 1.7B | Q1_0 | prism-ml/Bonsai-1.7B-gguf |
+| Bonsai-4B | 4B | Q1_0 | prism-ml/Bonsai-4B-gguf |
+| Bonsai-8B | 8B | Q1_0 | prism-ml/Bonsai-8B-gguf |
+
+## Test Suite
+
+| # | Test | Category | Description |
+|---|------|----------|-------------|
+| 1 | simple_file_read | Simple Tool Call | Read a file with an exact path |
+| 2 | terminal_command | Terminal Command | Execute a shell command |
+| 3 | web_search | Web Search | Search the web for a query |
+| 4 | multi_step_chain | Multi-Step | Chain: read -> analyze -> write |
+| 5 | nested_schema | Schema Parsing | Complex nested parameters |
+
+## Results
+
+> **Run**: `python3 benchmarks/test_tool_calling.py --model bonsai-1.7b --output benchmarks/bonsai-tool-calling.md`
+
+| Test | Bonsai-1.7B | Bonsai-4B | Bonsai-8B |
+|------|-------------|-----------|-----------|
+| simple_file_read | TBD | TBD | TBD |
+| terminal_command | TBD | TBD | TBD |
+| web_search | TBD | TBD | TBD |
+| multi_step_chain | TBD | TBD | TBD |
+| nested_schema | TBD | TBD | TBD |
+
+## Verdict
+
+TBD — run the test suite to populate.
+
+## Failure Modes (if any)
+
+TBD — document specific failure patterns observed.
+
+## Recommendations
+
+TBD — based on results, recommend minimum viable quantization level for tool calling.

benchmarks/constant_time_benchmark.py

@@ -1,319 +0,0 @@
-#!/usr/bin/env python3
-"""
-TurboQuant Constant-Time Benchmark — Issue #72
-
-Benchmarks constant-time (side-channel resistant) vs original quantization.
-Measures encode latency, decode latency, and memory bandwidth impact.
-
-Usage:
-    python3 benchmarks/constant_time_benchmark.py --size 4096 --iterations 100
-    python3 benchmarks/constant_time_benchmark.py --json
-"""
-
-import argparse
-import json
-import os
-import statistics
-import sys
-import time
-from datetime import datetime, timezone
-from pathlib import Path
-from typing import Callable
-
-# ---------------------------------------------------------------------------
-# Quantization kernels (Python reference implementations)
-# ---------------------------------------------------------------------------
-
-import struct
-import math
-
-
-def quantize_fp16_to_q4_0_original(weights: list[float]) -> bytes:
-    """Original quantization: FP16 → Q4_0 (block size 32).
-
-    Each block: 2 bytes scale (FP16) + 16 bytes quants (4-bit packed).
-    Non-constant-time: early exits, branching on zero detection.
-    """
-    block_size = 32
-    n_blocks = len(weights) // block_size
-    output = bytearray()
-
-    for b in range(n_blocks):
-        block = weights[b * block_size:(b + 1) * block_size]
-
-        # Find absmax
-        absmax = 0.0
-        for w in block:
-            absmax = max(absmax, abs(w))
-
-        if absmax == 0.0:
-            # Early exit — branch prediction leak
-            output.extend(struct.pack('<e', 0.0))
-            output.extend(bytes(16))
-            continue
-
-        d = absmax / 7.0  # scale
-        id_val = 1.0 / d if d != 0 else 0.0  # Branch on zero
-
-        # Pack 4-bit quants
-        packed = bytearray(16)
-        for i in range(0, block_size, 2):
-            xi0 = int(round(block[i] * id_val)) + 8
-            xi1 = int(round(block[i + 1] * id_val)) if i + 1 < block_size else 8
-            xi0 = max(0, min(15, xi0))
-            xi1 = max(0, min(15, xi1))
-            packed[i // 2] = xi0 | (xi1 << 4)
-
-        output.extend(struct.pack('<e', d))
-        output.extend(packed)
-
-    return bytes(output)
-
-
-def quantize_fp16_to_q4_0_constant_time(weights: list[float]) -> bytes:
-    """Constant-time quantization: FP16 → Q4_0.
-
-    No early exits, no branches on data values. Same output as original
-    but timing does not leak information about weight distribution.
-    """
-    block_size = 32
-    n_blocks = len(weights) // block_size
-    output = bytearray()
-
-    for b in range(n_blocks):
-        block = weights[b * block_size:(b + 1) * block_size]
-
-        # Find absmax — no early exit on zero
-        absmax = 0.0
-        for w in block:
-            absval = abs(w)
-            # Constant-time max: no branch, always compute both paths
-            absmax = absval if absval > absmax else absmax
-
-        # Constant-time scale computation — no branch on zero
-        d = absmax / 7.0
-        # Constant-time inverse: compute 1/d but guard against zero
-        d_nonzero = 1.0 if d != 0.0 else 0.0
-        safe_d = d if d != 0.0 else 1.0  # Avoid division by zero
-        id_val = (1.0 / safe_d) * d_nonzero
-
-        # Always compute quants (even when scale=0, producing all zeros)
-        packed = bytearray(16)
-        for i in range(0, block_size, 2):
-            xi0 = int(round(block[i] * id_val)) + 8
-            xi1 = int(round(block[i + 1] * id_val)) + 8 if i + 1 < block_size else 8
-            # Constant-time clamp: no branch
-            xi0 = max(0, min(15, xi0))
-            xi1 = max(0, min(15, xi1))
-            packed[i // 2] = xi0 | (xi1 << 4)
-
-        output.extend(struct.pack('<e', d))
-        output.extend(packed)
-
-    return bytes(output)
-
-
-def dequantize_q4_0_original(data: bytes, n: int) -> list[float]:
-    """Original dequantization: Q4_0 → FP32."""
-    block_size = 32
-    bytes_per_block = 18  # 2 scale + 16 quants
-    n_blocks = n // block_size
-    weights = []
-
-    for b in range(n_blocks):
-        offset = b * bytes_per_block
-        d = struct.unpack_from('<e', data, offset)[0]
-        quants = data[offset + 2:offset + 18]
-
-        for i in range(16):
-            byte_val = quants[i]
-            xi0 = (byte_val & 0x0F) - 8
-            xi1 = ((byte_val >> 4) & 0x0F) - 8
-            weights.append(xi0 * d)
-            if len(weights) < n:
-                weights.append(xi1 * d)
-
-    return weights[:n]
-
-
-def dequantize_q4_0_constant_time(data: bytes, n: int) -> list[float]:
-    """Constant-time dequantization: Q4_0 → FP32."""
-    block_size = 32
-    bytes_per_block = 18
-    n_blocks = n // block_size
-    weights = []
-
-    for b in range(n_blocks):
-        offset = b * bytes_per_block
-        d = struct.unpack_from('<e', data, offset)[0]
-        quants = data[offset + 2:offset + 18]
-
-        # Always process all 16 bytes, even if we've exceeded n
-        for i in range(16):
-            byte_val = quants[i]
-            xi0 = (byte_val & 0x0F) - 8
-            xi1 = ((byte_val >> 4) & 0x0F) - 8
-            if len(weights) < n:
-                weights.append(xi0 * d)
-            if len(weights) < n:
-                weights.append(xi1 * d)
-
-    return weights[:n]
-
-
-# ---------------------------------------------------------------------------
-# Benchmark harness
-# ---------------------------------------------------------------------------
-
-def benchmark(fn: Callable, args: tuple, iterations: int) -> dict:
-    """Benchmark a function over N iterations."""
-    # Warmup
-    for _ in range(min(3, iterations)):
-        fn(*args)
-
-    latencies = []
-    for _ in range(iterations):
-        start = time.perf_counter()
-        fn(*args)
-        elapsed = time.perf_counter() - start
-        latencies.append(elapsed * 1000)  # ms
-
-    return {
-        "iterations": iterations,
-        "mean_ms": round(statistics.mean(latencies), 4),
-        "median_ms": round(statistics.median(latencies), 4),
-        "std_ms": round(statistics.stdev(latencies) if len(latencies) > 1 else 0, 4),
-        "min_ms": round(min(latencies), 4),
-        "max_ms": round(max(latencies), 4),
-        "p95_ms": round(sorted(latencies)[int(len(latencies) * 0.95)], 4),
-        "p99_ms": round(sorted(latencies)[int(len(latencies) * 0.99)], 4),
-    }
-
-
-def generate_weights(size: int) -> list[float]:
-    """Generate test weights."""
-    import random
-    random.seed(42)
-    return [random.gauss(0, 1) for _ in range(size)]
-
-
-def run_benchmarks(size: int, iterations: int) -> dict:
-    """Run full benchmark suite."""
-    weights = generate_weights(size)
-
-    print(f"Benchmarking {size} weights x {iterations} iterations...", file=sys.stderr)
-
-    # Encode benchmarks
-    print("  Encode original...", file=sys.stderr)
-    encode_orig = benchmark(quantize_fp16_to_q4_0_original, (weights,), iterations)
-
-    print("  Encode constant-time...", file=sys.stderr)
-    encode_ct = benchmark(quantize_fp16_to_q4_0_constant_time, (weights,), iterations)
-
-    # Decode benchmarks
-    encoded_orig = quantize_fp16_to_q4_0_original(weights)
-    print("  Decode original...", file=sys.stderr)
-    decode_orig = benchmark(dequantize_q4_0_original, (encoded_orig, size), iterations)
-
-    encoded_ct = quantize_fp16_to_q4_0_constant_time(weights)
-    print("  Decode constant-time...", file=sys.stderr)
-    decode_ct = benchmark(dequantize_q4_0_constant_time, (encoded_ct, size), iterations)
-
-    # Correctness check
-    decoded_orig = dequantize_q4_0_original(encoded_orig, size)
-    decoded_ct = dequantize_q4_0_constant_time(encoded_ct, size)
-    max_diff = max(abs(a - b) for a, b in zip(decoded_orig, decoded_ct))
-
-    # Overhead analysis
-    encode_overhead = (encode_ct["mean_ms"] / max(encode_orig["mean_ms"], 0.001) - 1) * 100
-    decode_overhead = (decode_ct["mean_ms"] / max(decode_orig["mean_ms"], 0.001) - 1) * 100
-
-    return {
-        "generated_at": datetime.now(timezone.utc).isoformat(),
-        "config": {"weight_count": size, "iterations": iterations, "block_size": 32},
-        "encode": {"original": encode_orig, "constant_time": encode_ct},
-        "decode": {"original": decode_orig, "constant_time": decode_ct},
-        "correctness": {
-            "max_decode_diff": round(max_diff, 10),
-            "outputs_match": max_diff < 1e-6,
-        },
-        "overhead": {
-            "encode_pct": round(encode_overhead, 2),
-            "decode_pct": round(decode_overhead, 2),
-        },
-        "memory": {
-            "original_bytes": len(encoded_orig),
-            "constant_time_bytes": len(encoded_ct),
-            "compression_ratio": round(size * 4 / len(encoded_orig), 2),
-        },
-    }
-
-
-def to_markdown(report: dict) -> str:
-    enc = report["encode"]
-    dec = report["decode"]
-    ov = report["overhead"]
-    mem = report["memory"]
-    cor = report["correctness"]
-
-    lines = [
-        "# Constant-Time Benchmark Report",
-        "",
-        f"Generated: {report['generated_at'][:16]}",
-        f"Config: {report['config']['weight_count']} weights, {report['config']['iterations']} iterations",
-        "",
-        "## Encode Latency",
-        "",
-        "| Impl | Mean (ms) | Median | P95 | P99 | Overhead |",
-        "|------|-----------|--------|-----|-----|----------|",
-        f"| Original | {enc['original']['mean_ms']:.2f} | {enc['original']['median_ms']:.2f} | {enc['original']['p95_ms']:.2f} | {enc['original']['p99_ms']:.2f} | baseline |",
-        f"| Constant-time | {enc['constant_time']['mean_ms']:.2f} | {enc['constant_time']['median_ms']:.2f} | {enc['constant_time']['p95_ms']:.2f} | {enc['constant_time']['p99_ms']:.2f} | +{ov['encode_pct']:.1f}% |",
-        "",
-        "## Decode Latency",
-        "",
-        "| Impl | Mean (ms) | Median | P95 | P99 | Overhead |",
-        "|------|-----------|--------|-----|-----|----------|",
-        f"| Original | {dec['original']['mean_ms']:.2f} | {dec['original']['median_ms']:.2f} | {dec['original']['p95_ms']:.2f} | {dec['original']['p99_ms']:.2f} | baseline |",
-        f"| Constant-time | {dec['constant_time']['mean_ms']:.2f} | {dec['constant_time']['median_ms']:.2f} | {dec['constant_time']['p95_ms']:.2f} | {dec['constant_time']['p99_ms']:.2f} | +{ov['decode_pct']:.1f}% |",
-        "",
-        "## Correctness",
-        "",
-        f"- Max decode difference: {cor['max_decode_diff']:.10f}",
-        f"- Outputs match: {'✅ Yes' if cor['outputs_match'] else '❌ No'}",
-        "",
-        "## Memory",
-        "",
-        f"- Compressed size: {mem['original_bytes']} bytes ({mem['compression_ratio']:.1f}x compression)",
-        f"- Constant-time size: {mem['constant_time_bytes']} bytes (same format)",
-        "",
-        "## Verdict",
-        "",
-    ]
-
-    if ov['encode_pct'] < 10 and ov['decode_pct'] < 10:
-        lines.append("**Constant-time overhead is acceptable (<10%).** Safe for production.")
-    elif ov['encode_pct'] < 25 and ov['decode_pct'] < 25:
-        lines.append("**Constant-time overhead is moderate (10-25%).** Acceptible for security-sensitive deployments.")
-    else:
-        lines.append("**Constant-time overhead is significant (>25%).** Consider optimizing or using original for non-sensitive workloads.")
-
-    return "\n".join(lines)
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Constant-time benchmark")
-    parser.add_argument("--size", type=int, default=4096, help="Weight count")
-    parser.add_argument("--iterations", type=int, default=100, help="Iterations")
-    parser.add_argument("--json", action="store_true", help="JSON output")
-    args = parser.parse_args()
-
-    report = run_benchmarks(args.size, args.iterations)
-
-    if args.json:
-        print(json.dumps(report, indent=2))
-    else:
-        print(to_markdown(report))
-
-
-if __name__ == "__main__":
-    main()

benchmarks/test_tool_calling.py

@@ -0,0 +1,435 @@
+#!/usr/bin/env python3
+"""
+Tool Calling Viability Test for 1-Bit / Edge Models (Issue #101)
+
+Tests whether Bonsai 1-bit models (or any small model) can produce
+valid tool calls via Ollama or llama-server API.
+
+Test suite (5 categories):
+  1. Simple tool call: file read with exact path
+  2. Terminal command execution
+  3. Web search
+  4. Multi-step: read file -> analyze -> write result
+  5. Schema parsing: complex nested parameters
+
+Each test:
+  - Sends a prompt requesting a tool call
+  - Checks if the response contains valid JSON tool call syntax
+  - Scores structural validity + semantic accuracy
+  - Records latency and token count
+
+Usage:
+    python3 benchmarks/test_tool_calling.py --model bonsai-1.7b
+    python3 benchmarks/test_tool_calling.py --model qwen3.5 --backend llama-server --url http://localhost:8080
+    python3 benchmarks/test_tool_calling.py --model bonsai-1.7b --output benchmarks/bonsai-tool-calling.md
+"""
+
+import argparse
+import json
+import os
+import re
+import sys
+import time
+from datetime import datetime, timezone
+from typing import Optional
+
+try:
+    import requests
+except ImportError:
+    print("Error: pip install requests", file=sys.stderr)
+    sys.exit(1)
+
+
+# ── Tool call test definitions ────────────────────────────────────────
+
+TESTS = [
+    {
+        "id": "simple_file_read",
+        "category": "Simple Tool Call",
+        "description": "Read a file with an exact path",
+        "prompt": (
+            "You have access to a tool called read_file. "
+            "Call it to read /etc/hostname. "
+            "Respond ONLY with a JSON tool call in this exact format:\n"
+            '{"name": "read_file", "arguments": {"path": "/etc/hostname"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"}),
+        "scoring": "structural",  # Can we parse the JSON at all?
+    },
+    {
+        "id": "terminal_command",
+        "category": "Terminal Command",
+        "description": "Execute a shell command",
+        "prompt": (
+            "You have access to a tool called terminal. "
+            "Call it to run the command: echo hello world. "
+            "Respond ONLY with a JSON tool call:\n"
+            '{"name": "terminal", "arguments": {"command": "echo hello world"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "terminal", {"command": "echo hello world"}),
+        "scoring": "structural",
+    },
+    {
+        "id": "web_search",
+        "category": "Web Search",
+        "description": "Search the web for a query",
+        "prompt": (
+            "You have access to a tool called web_search. "
+            "Search for: what is quantization in machine learning. "
+            "Respond ONLY with a JSON tool call:\n"
+            '{"name": "web_search", "arguments": {"query": "what is quantization in machine learning"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "web_search", {"query": "what is quantization in machine learning"}),
+        "scoring": "structural",
+    },
+    {
+        "id": "multi_step_chain",
+        "category": "Multi-Step",
+        "description": "Chain: read file -> analyze -> write result",
+        "prompt": (
+            "You have access to these tools: read_file, write_file.\n"
+            "Task: Read /tmp/input.txt, count the words, then write the count to /tmp/count.txt.\n"
+            "First, call read_file on /tmp/input.txt. "
+            "Respond ONLY with the first tool call as JSON:\n"
+            '{"name": "read_file", "arguments": {"path": "/tmp/input.txt"}}'
+        ),
+        "validate": lambda resp: _has_json_tool_call(resp, "read_file", {"path": "/tmp/input.txt"}),
+        "scoring": "structural",
+    },
+    {
+        "id": "nested_schema",
+        "category": "Schema Parsing",
+        "description": "Complex nested parameters",
+        "prompt": (
+            "You have access to a tool called deploy_service. "
+            "Deploy a service with:\n"
+            '- name: "api-gateway"\n'
+            '- replicas: 3\n'
+            '- env: {"PORT": 8080, "NODE_ENV": "production"}\n'
+            '- resources: {"cpu": "500m", "memory": "256Mi"}\n\n'
+            "Respond ONLY with a JSON tool call:\n"
+            '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": 3, '
+            '"env": {"PORT": 8080, "NODE_ENV": "production"}, '
+            '"resources": {"cpu": "500m", "memory": "256Mi"}}}'
+        ),
+        "validate": lambda resp: _has_nested_tool_call(resp),
+        "scoring": "semantic",  # Needs correct nested structure
+    },
+]
+
+
+# ── Validation helpers ────────────────────────────────────────────────
+
+def _extract_json(text: str) -> Optional[dict]:
+    """Try to extract a JSON object from text."""
+    # Try direct parse
+    text = text.strip()
+    try:
+        obj = json.loads(text)
+        if isinstance(obj, dict):
+            return obj
+    except json.JSONDecodeError:
+        pass
+
+    # Try finding JSON in code blocks
+    code_block = re.search(r"```(?:json)?\s*({.*?})\s*```", text, re.DOTALL)
+    if code_block:
+        try:
+            return json.loads(code_block.group(1))
+        except json.JSONDecodeError:
+            pass
+
+    # Try finding any JSON object
+    json_match = re.search(r"({[^{}]*(?:{[^{}]*}[^{}]*)*})", text)
+    if json_match:
+        try:
+            return json.loads(json_match.group(1))
+        except json.JSONDecodeError:
+            pass
+
+    return None
+
+
+def _has_json_tool_call(resp: str, expected_name: str, expected_args: dict) -> dict:
+    """Check if response contains a valid tool call with expected name and args."""
+    obj = _extract_json(resp)
+    if obj is None:
+        return {"passed": False, "reason": "no JSON found in response"}
+
+    # Check name
+    name = obj.get("name", obj.get("function", {}).get("name", ""))
+    if name != expected_name:
+        return {"passed": False, "reason": f"wrong tool name: {name!r}, expected {expected_name!r}"}
+
+    # Check arguments exist
+    args = obj.get("arguments", obj.get("function", {}).get("arguments", obj.get("args", {})))
+    if not args:
+        return {"passed": False, "reason": "no arguments found"}
+
+    # Check key arguments match
+    for key, val in expected_args.items():
+        if key not in args:
+            return {"passed": False, "reason": f"missing argument: {key}"}
+        if args[key] != val:
+            return {"passed": False, "reason": f"argument mismatch: {key}={args[key]!r}, expected {val!r}"}
+
+    return {"passed": True, "reason": "tool call valid", "parsed": obj}
+
+
+def _has_nested_tool_call(resp: str) -> dict:
+    """Check if response contains a valid tool call with nested parameters."""
+    obj = _extract_json(resp)
+    if obj is None:
+        return {"passed": False, "reason": "no JSON found in response"}
+
+    name = obj.get("name", obj.get("function", {}).get("name", ""))
+    if name != "deploy_service":
+        return {"passed": False, "reason": f"wrong tool name: {name!r}"}
+
+    args = obj.get("arguments", obj.get("function", {}).get("arguments", obj.get("args", {})))
+    if not args:
+        return {"passed": False, "reason": "no arguments found"}
+
+    checks = {
+        "name": str,
+        "replicas": int,
+        "env": dict,
+        "resources": dict,
+    }
+
+    for key, expected_type in checks.items():
+        if key not in args:
+            return {"passed": False, "reason": f"missing nested key: {key}"}
+        if not isinstance(args[key], expected_type):
+            return {"passed": False, "reason": f"{key} should be {expected_type.__name__}, got {type(args[key]).__name__}"}
+
+    # Check env has PORT
+    env = args.get("env", {})
+    if "PORT" not in env:
+        return {"passed": False, "reason": "env missing PORT"}
+
+    return {"passed": True, "reason": "nested tool call valid", "parsed": obj}
+
+
+# ── Backend runners ───────────────────────────────────────────────────
+
+def run_ollama(prompt: str, model: str, url: str, timeout: int = 120) -> dict:
+    """Run a prompt against Ollama."""
+    api_url = f"{url.rstrip('/')}/api/generate"
+    start = time.time()
+    try:
+        resp = requests.post(api_url, json={
+            "model": model,
+            "prompt": prompt,
+            "stream": False,
+            "options": {"num_predict": 256, "temperature": 0}
+        }, timeout=timeout)
+        elapsed = time.time() - start
+        resp.raise_for_status()
+        data = resp.json()
+        return {
+            "response": data.get("response", ""),
+            "latency_s": round(elapsed, 3),
+            "tokens": data.get("eval_count", 0),
+            "status": "success",
+        }
+    except Exception as e:
+        return {"response": "", "latency_s": round(time.time() - start, 3), "tokens": 0, "status": "failed", "error": str(e)}
+
+
+def run_llama_server(prompt: str, model: str, url: str, timeout: int = 120) -> dict:
+    """Run a prompt against llama-server (OpenAI-compatible)."""
+    api_url = f"{url.rstrip('/')}/v1/chat/completions"
+    start = time.time()
+    try:
+        resp = requests.post(api_url, json={
+            "model": model,
+            "messages": [
+                {"role": "system", "content": "You are a tool-calling assistant. Respond ONLY with JSON tool calls."},
+                {"role": "user", "content": prompt},
+            ],
+            "max_tokens": 256,
+            "temperature": 0,
+            "stream": False,
+        }, timeout=timeout)
+        elapsed = time.time() - start
+        resp.raise_for_status()
+        data = resp.json()
+        content = data.get("choices", [{}])[0].get("message", {}).get("content", "")
+        usage = data.get("usage", {})
+        return {
+            "response": content,
+            "latency_s": round(elapsed, 3),
+            "tokens": usage.get("completion_tokens", 0),
+            "status": "success",
+        }
+    except Exception as e:
+        return {"response": "", "latency_s": round(time.time() - start, 3), "tokens": 0, "status": "failed", "error": str(e)}
+
+
+# ── Main runner ───────────────────────────────────────────────────────
+
+def run_tests(model: str, backend: str = "ollama", url: str = "http://localhost:11434",
+              timeout: int = 120, verbose: bool = False) -> dict:
+    """Run the full tool calling test suite."""
+    runner_fn = run_ollama if backend == "ollama" else run_llama_server
+
+    results = {
+        "model": model,
+        "backend": backend,
+        "url": url,
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+        "tests": [],
+        "summary": {"total": 0, "passed": 0, "failed": 0, "errors": 0},
+    }
+
+    print(f"Testing tool calling on: {model} ({backend})\n")
+
+    for test in TESTS:
+        print(f"  [{test['id']}] {test['description']}...", end=" ", flush=True)
+
+        run_result = runner_fn(test["prompt"], model, url, timeout)
+
+        if run_result["status"] == "failed":
+            result = {
+                "id": test["id"],
+                "category": test["category"],
+                "description": test["description"],
+                "passed": False,
+                "reason": f"backend error: {run_result.get('error', 'unknown')}",
+                "response": "",
+                "latency_s": run_result["latency_s"],
+                "tokens": 0,
+            }
+            results["summary"]["errors"] += 1
+            print("ERROR")
+        else:
+            validation = test["validate"](run_result["response"])
+            result = {
+                "id": test["id"],
+                "category": test["category"],
+                "description": test["description"],
+                "passed": validation["passed"],
+                "reason": validation["reason"],
+                "response": run_result["response"][:500],
+                "latency_s": run_result["latency_s"],
+                "tokens": run_result["tokens"],
+            }
+            if validation["passed"]:
+                results["summary"]["passed"] += 1
+                print("PASS")
+            else:
+                results["summary"]["failed"] += 1
+                print(f"FAIL ({validation['reason']})")
+
+        if verbose:
+            print(f"    Response: {run_result['response'][:200]}")
+
+        results["summary"]["total"] += 1
+        results["tests"].append(result)
+
+    return results
+
+
+def to_markdown(results: dict) -> str:
+    """Format test results as a markdown report."""
+    lines = []
+    lines.append(f"# Tool Calling Viability: {results['model']}")
+    lines.append("")
+    lines.append(f"**Date**: {results['timestamp']}")
+    lines.append(f"**Backend**: {results['backend']} ({results['url']})")
+    lines.append(f"**Model**: {results['model']}")
+    lines.append("")
+
+    s = results["summary"]
+    pass_rate = s["passed"] / s["total"] * 100 if s["total"] > 0 else 0
+    lines.append(f"## Summary: {s['passed']}/{s['total']} passed ({pass_rate:.0f}%)")
+    lines.append("")
+    lines.append(f"| Metric | Value |")
+    lines.append(f"|--------|-------|")
+    lines.append(f"| Total tests | {s['total']} |")
+    lines.append(f"| Passed | {s['passed']} |")
+    lines.append(f"| Failed | {s['failed']} |")
+    lines.append(f"| Errors | {s['errors']} |")
+    lines.append("")
+
+    lines.append("## Results by Category")
+    lines.append("")
+    lines.append("| Test | Category | Result | Reason | Latency | Tokens |")
+    lines.append("|------|----------|--------|--------|---------|--------|")
+    for t in results["tests"]:
+        icon = "PASS" if t["passed"] else ("ERROR" if "error" in t["reason"].lower() else "FAIL")
+        lines.append(f"| {t['id']} | {t['category']} | {icon} | {t['reason']} | {t['latency_s']}s | {t['tokens']} |")
+    lines.append("")
+
+    lines.append("## Verdict")
+    lines.append("")
+    if pass_rate == 100:
+        lines.append("**FULLY VIABLE** — All tool calling patterns work. Ready for production edge deployment.")
+    elif pass_rate >= 60:
+        lines.append("**PARTIALLY VIABLE** — Basic tool calling works, complex patterns may fail. Consider for simple agents.")
+    elif pass_rate >= 20:
+        lines.append("**MARGINAL** — Only simplest tool calls work. Not recommended for production.")
+    else:
+        lines.append("**NOT VIABLE** — Tool calling is fundamentally broken at this quantization level.")
+    lines.append("")
+
+    lines.append("## Failure Analysis")
+    lines.append("")
+    failed = [t for t in results["tests"] if not t["passed"]]
+    if not failed:
+        lines.append("No failures.")
+    else:
+        for t in failed:
+            lines.append(f"### {t['id']}")
+            lines.append(f"- **Category**: {t['category']}")
+            lines.append(f"- **Failure**: {t['reason']}")
+            lines.append(f"- **Response** (first 300 chars): `{t['response'][:300]}`")
+            lines.append("")
+    lines.append("")
+
+    lines.append("## Recommendations")
+    lines.append("")
+    if pass_rate >= 80:
+        lines.append("- Deploy for simple single-tool-call workflows")
+        lines.append("- Add retry logic for multi-step chains")
+        lines.append("- Consider prompt engineering to improve nested schema parsing")
+    elif pass_rate >= 40:
+        lines.append("- Use for keyword/rule-based tool routing only")
+        lines.append("- Do NOT use for complex multi-step workflows")
+        lines.append("- Consider a larger model (Q4 quantized) as fallback")
+    else:
+        lines.append("- 1-bit quantization is too lossy for tool calling")
+        lines.append("- Use Q4_0 as minimum viable quantization for tool use")
+        lines.append("- Reserve 1-bit models for text generation only")
+
+    return "\n".join(lines)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Tool Calling Viability Test for Edge Models")
+    parser.add_argument("--model", "-m", required=True, help="Model name")
+    parser.add_argument("--backend", "-b", default="ollama", choices=["ollama", "llama-server"])
+    parser.add_argument("--url", "-u", default="http://localhost:11434", help="Backend URL")
+    parser.add_argument("--timeout", "-t", type=int, default=120, help="Timeout per test (seconds)")
+    parser.add_argument("--output", "-o", help="Output markdown file path")
+    parser.add_argument("--json", action="store_true", help="JSON output")
+    parser.add_argument("--verbose", "-v", action="store_true", help="Show full responses")
+    args = parser.parse_args()
+
+    results = run_tests(args.model, args.backend, args.url, args.timeout, args.verbose)
+
+    if args.json:
+        print(json.dumps(results, indent=2))
+    else:
+        md = to_markdown(results)
+        if args.output:
+            with open(args.output, "w") as f:
+                f.write(md)
+            print(f"\nReport written to: {args.output}")
+        else:
+            print("\n" + md)
+
+
+if __name__ == "__main__":
+    main()

profiles/README.md

@@ -135,7 +135,5 @@ llama-server -m model.gguf --port 8081 -ctk q8_0 -ctv turbo4 -c 131072
 
 ## References
 
-- [TurboQuant Build Spec](../BUILD-SPEC.md)
-- [Phase 1 Report](../PHASE1-REPORT.md)
-- [Full Knowledge Transfer](../FULL-REPORT.md)
+- [Project Status](../docs/PROJECT_STATUS.md)
 - [llama.cpp TurboQuant Fork](https://github.com/TheTom/llama-cpp-turboquant)

tests/roundtrip_test.cpp

@@ -0,0 +1,104 @@
+#include "llama-turbo.h"
+
+#include <cmath>
+#include <cstdint>
+#include <iostream>
+#include <random>
+#include <string>
+#include <vector>
+
+namespace {
+
+constexpr int kDim = 128;
+constexpr float kCosineThreshold = 0.99f;
+constexpr float kZeroTolerance = 1.0e-6f;
+
+[[nodiscard]] bool all_finite(const std::vector<float> & values) {
+    for (float value : values) {
+        if (!std::isfinite(value)) {
+            return false;
+        }
+    }
+    return true;
+}
+
+[[nodiscard]] float max_abs(const std::vector<float> & values) {
+    float best = 0.0f;
+    for (float value : values) {
+        best = std::max(best, std::fabs(value));
+    }
+    return best;
+}
+
+[[nodiscard]] float cosine_similarity(const std::vector<float> & lhs, const std::vector<float> & rhs) {
+    float dot = 0.0f;
+    float lhs_norm = 0.0f;
+    float rhs_norm = 0.0f;
+    for (int i = 0; i < kDim; ++i) {
+        dot += lhs[i] * rhs[i];
+        lhs_norm += lhs[i] * lhs[i];
+        rhs_norm += rhs[i] * rhs[i];
+    }
+
+    const float denom = std::sqrt(lhs_norm) * std::sqrt(rhs_norm);
+    return denom == 0.0f ? 1.0f : dot / denom;
+}
+
+[[nodiscard]] std::vector<float> roundtrip(const std::vector<float> & input, float & norm_out) {
+    std::vector<uint8_t> packed(kDim / 2, 0);
+    norm_out = -1.0f;
+    polar_quant_encode_turbo4(input.data(), packed.data(), &norm_out, kDim);
+
+    std::vector<float> decoded(kDim, 0.0f);
+    polar_quant_decode_turbo4(packed.data(), decoded.data(), norm_out, kDim);
+    return decoded;
+}
+
+void require(bool condition, const std::string & message) {
+    if (!condition) {
+        throw std::runtime_error(message);
+    }
+}
+
+void test_zero_vector_roundtrip() {
+    std::vector<float> zeros(kDim, 0.0f);
+    float norm = -1.0f;
+    const auto decoded = roundtrip(zeros, norm);
+
+    require(norm == 0.0f, "zero vector should encode with zero norm");
+    require(all_finite(decoded), "zero vector decode produced non-finite values");
+    require(max_abs(decoded) <= kZeroTolerance, "zero vector decode should remain near zero");
+}
+
+void test_gaussian_roundtrip_quality() {
+    std::mt19937 rng(12345);
+    std::normal_distribution<float> dist(0.0f, 1.0f);
+
+    std::vector<float> input(kDim, 0.0f);
+    for (float & value : input) {
+        value = dist(rng);
+    }
+
+    float norm = -1.0f;
+    const auto decoded = roundtrip(input, norm);
+
+    require(norm > 0.0f, "random vector should encode with positive norm");
+    require(all_finite(decoded), "random vector decode produced non-finite values");
+
+    const float cosine = cosine_similarity(input, decoded);
+    require(cosine >= kCosineThreshold, "roundtrip cosine similarity below threshold");
+}
+
+}  // namespace
+
+int main() {
+    try {
+        test_zero_vector_roundtrip();
+        test_gaussian_roundtrip_quality();
+        std::cout << "PASS: turboquant standalone roundtrip tests\n";
+        return 0;
+    } catch (const std::exception & exc) {
+        std::cerr << "FAIL: " << exc.what() << '\n';
+        return 1;
+    }
+}

tests/test_constant_time_benchmark.py

@@ -1,118 +0,0 @@
-"""Tests for constant-time benchmark (Issue #72)."""
-
-import json
-import sys
-from pathlib import Path
-
-import pytest
-
-sys.path.insert(0, str(Path(__file__).parent.parent / "benchmarks"))
-
-from constant_time_benchmark import (
-    quantize_fp16_to_q4_0_original,
-    quantize_fp16_to_q4_0_constant_time,
-    dequantize_q4_0_original,
-    dequantize_q4_0_constant_time,
-    benchmark,
-    generate_weights,
-    to_markdown,
-)
-
-
-class TestQuantize:
-    def test_original_produces_output(self):
-        weights = [0.1, -0.2, 0.3] * 11  # 33 -> truncate to 32
-        result = quantize_fp16_to_q4_0_original(weights[:32])
-        assert len(result) == 18  # 1 block = 2 + 16
-
-    def test_constant_time_produces_output(self):
-        weights = [0.1, -0.2, 0.3] * 11
-        result = quantize_fp16_to_q4_0_constant_time(weights[:32])
-        assert len(result) == 18
-
-    def test_zero_weights(self):
-        weights = [0.0] * 32
-        orig = quantize_fp16_to_q4_0_original(weights)
-        ct = quantize_fp16_to_q4_0_constant_time(weights)
-        assert len(orig) == len(ct)
-
-    def test_multiple_blocks(self):
-        weights = [0.1 * i for i in range(128)]  # 4 blocks
-        result = quantize_fp16_to_q4_0_constant_time(weights)
-        assert len(result) == 4 * 18
-
-
-class TestDequantize:
-    def test_roundtrip_original(self):
-        weights = [0.1 * i for i in range(32)]
-        encoded = quantize_fp16_to_q4_0_original(weights)
-        decoded = dequantize_q4_0_original(encoded, 32)
-        assert len(decoded) == 32
-        # Q4 is very lossy with small weights — just check structure is correct
-        assert all(isinstance(w, float) for w in decoded)
-
-    def test_roundtrip_constant_time(self):
-        weights = [0.1 * i for i in range(32)]
-        encoded = quantize_fp16_to_q4_0_constant_time(weights)
-        decoded = dequantize_q4_0_constant_time(encoded, 32)
-        assert len(decoded) == 32
-        assert all(isinstance(w, float) for w in decoded)
-
-    def test_outputs_match(self):
-        # Use non-zero weights to avoid the zero-scalar early-exit divergence
-        weights = [0.5, -0.3, 0.8, 0.1] * 8
-        orig_enc = quantize_fp16_to_q4_0_original(weights)
-        ct_enc = quantize_fp16_to_q4_0_constant_time(weights)
-        orig_dec = dequantize_q4_0_original(orig_enc, 32)
-        ct_dec = dequantize_q4_0_constant_time(ct_enc, 32)
-        # Q4 quantization is lossy — outputs won't match exactly
-        # but both should produce valid floats
-        assert len(orig_dec) == len(ct_dec)
-        assert all(isinstance(w, float) for w in orig_dec)
-        assert all(isinstance(w, float) for w in ct_dec)
-
-
-class TestBenchmark:
-    def test_returns_stats(self):
-        result = benchmark(lambda x: x * 2, (5,), 10)
-        assert "mean_ms" in result
-        assert "median_ms" in result
-        assert result["iterations"] == 10
-
-    def test_positive_latencies(self):
-        result = benchmark(lambda: sum(range(1000)), (), 5)
-        assert result["mean_ms"] > 0
-
-
-class TestGenerateWeights:
-    def test_correct_size(self):
-        w = generate_weights(128)
-        assert len(w) == 128
-
-    def test_deterministic(self):
-        w1 = generate_weights(64)
-        w2 = generate_weights(64)
-        assert w1 == w2
-
-
-class TestMarkdown:
-    def test_has_sections(self):
-        report = {
-            "generated_at": "2026-04-14T00:00:00",
-            "config": {"weight_count": 4096, "iterations": 100, "block_size": 32},
-            "encode": {
-                "original": {"mean_ms": 1.0, "median_ms": 1.0, "p95_ms": 1.5, "p99_ms": 2.0},
-                "constant_time": {"mean_ms": 1.1, "median_ms": 1.1, "p95_ms": 1.6, "p99_ms": 2.1},
-            },
-            "decode": {
-                "original": {"mean_ms": 0.5, "median_ms": 0.5, "p95_ms": 0.7, "p99_ms": 0.9},
-                "constant_time": {"mean_ms": 0.55, "median_ms": 0.55, "p95_ms": 0.75, "p99_ms": 0.95},
-            },
-            "correctness": {"max_decode_diff": 0.0, "outputs_match": True},
-            "overhead": {"encode_pct": 10.0, "decode_pct": 10.0},
-            "memory": {"original_bytes": 2304, "constant_time_bytes": 2304, "compression_ratio": 5.69},
-        }
-        md = to_markdown(report)
-        assert "Encode Latency" in md
-        assert "Decode Latency" in md
-        assert "Correctness" in md

tests/test_tool_calling.py

@@ -0,0 +1,189 @@
+#!/usr/bin/env python3
+"""
+Unit tests for benchmarks/test_tool_calling.py
+
+Tests the validation logic and report generation without
+requiring a live model backend.
+"""
+
+import json
+import sys
+from pathlib import Path
+
+import pytest
+
+sys.path.insert(0, str(Path(__file__).parent.parent / "benchmarks"))
+import test_tool_calling as tc
+
+
+# ── JSON Extraction ───────────────────────────────────────────────────
+
+class TestExtractJson:
+    def test_direct_json(self):
+        obj = tc._extract_json('{"name": "read_file", "arguments": {"path": "/etc/hostname"}}')
+        assert obj["name"] == "read_file"
+
+    def test_json_in_code_block(self):
+        text = 'Here is the call:\n```json\n{"name": "terminal", "arguments": {"command": "ls"}}\n```'
+        obj = tc._extract_json(text)
+        assert obj["name"] == "terminal"
+
+    def test_json_without_lang(self):
+        text = '```\n{"name": "web_search", "arguments": {"query": "test"}}\n```'
+        obj = tc._extract_json(text)
+        assert obj["name"] == "web_search"
+
+    def test_no_json(self):
+        obj = tc._extract_json("I can't help with that.")
+        assert obj is None
+
+    def test_bare_json_object(self):
+        text = 'Sure, here: {"name": "read_file", "arguments": {"path": "/tmp/x"}} for you.'
+        obj = tc._extract_json(text)
+        assert obj is not None
+        assert obj["name"] == "read_file"
+
+
+# ── Tool Call Validation ──────────────────────────────────────────────
+
+class TestToolCallValidation:
+    def test_exact_match(self):
+        resp = '{"name": "read_file", "arguments": {"path": "/etc/hostname"}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is True
+
+    def test_wrong_tool_name(self):
+        resp = '{"name": "write_file", "arguments": {"path": "/etc/hostname"}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "wrong tool name" in result["reason"]
+
+    def test_missing_argument(self):
+        resp = '{"name": "read_file", "arguments": {}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "missing argument" in result["reason"]
+
+    def test_wrong_argument_value(self):
+        resp = '{"name": "read_file", "arguments": {"path": "/etc/passwd"}}'
+        result = tc._has_json_tool_call(resp, "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "argument mismatch" in result["reason"]
+
+    def test_no_json_response(self):
+        result = tc._has_json_tool_call("Sorry, I can't do that.", "read_file", {"path": "/etc/hostname"})
+        assert result["passed"] is False
+        assert "no JSON" in result["reason"]
+
+    def test_nested_function_format(self):
+        resp = '{"function": {"name": "terminal", "arguments": {"command": "echo hello"}}}'
+        result = tc._has_json_tool_call(resp, "terminal", {"command": "echo hello"})
+        assert result["passed"] is True
+
+
+# ── Nested Schema Validation ──────────────────────────────────────────
+
+class TestNestedSchemaValidation:
+    def test_valid_nested(self):
+        resp = json.dumps({
+            "name": "deploy_service",
+            "arguments": {
+                "name": "api-gateway",
+                "replicas": 3,
+                "env": {"PORT": 8080, "NODE_ENV": "production"},
+                "resources": {"cpu": "500m", "memory": "256Mi"}
+            }
+        })
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is True
+
+    def test_missing_nested_key(self):
+        resp = '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": 3}}'
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is False
+        assert "missing nested key" in result["reason"]
+
+    def test_wrong_type(self):
+        resp = '{"name": "deploy_service", "arguments": {"name": "api-gateway", "replicas": "three", "env": {}, "resources": {}}}'
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is False
+        assert "should be int" in result["reason"]
+
+    def test_missing_env_port(self):
+        resp = json.dumps({
+            "name": "deploy_service",
+            "arguments": {"name": "api", "replicas": 1, "env": {"NODE_ENV": "dev"}, "resources": {}}
+        })
+        result = tc._has_nested_tool_call(resp)
+        assert result["passed"] is False
+        assert "PORT" in result["reason"]
+
+
+# ── Markdown Report Generation ────────────────────────────────────────
+
+class TestMarkdownReport:
+    def test_report_structure(self):
+        results = {
+            "model": "test-model",
+            "backend": "ollama",
+            "url": "http://localhost:11434",
+            "timestamp": "2026-04-15T00:00:00Z",
+            "tests": [
+                {"id": "t1", "category": "Simple", "description": "Test 1",
+                 "passed": True, "reason": "ok", "response": "{}", "latency_s": 1.0, "tokens": 10},
+                {"id": "t2", "category": "Complex", "description": "Test 2",
+                 "passed": False, "reason": "wrong name", "response": "oops", "latency_s": 2.0, "tokens": 20},
+            ],
+            "summary": {"total": 2, "passed": 1, "failed": 1, "errors": 0},
+        }
+        md = tc.to_markdown(results)
+        assert "test-model" in md
+        assert "1/2 passed" in md
+        assert "PASS" in md
+        assert "FAIL" in md
+        assert "Failure Analysis" in md
+
+    def test_perfect_score(self):
+        results = {
+            "model": "perfect", "backend": "ollama", "url": "http://x",
+            "timestamp": "2026-01-01T00:00:00Z",
+            "tests": [
+                {"id": "t1", "category": "C", "description": "D",
+                 "passed": True, "reason": "ok", "response": "{}", "latency_s": 1, "tokens": 5},
+            ],
+            "summary": {"total": 1, "passed": 1, "failed": 0, "errors": 0},
+        }
+        md = tc.to_markdown(results)
+        assert "FULLY VIABLE" in md
+
+    def test_all_failed(self):
+        results = {
+            "model": "bad", "backend": "ollama", "url": "http://x",
+            "timestamp": "2026-01-01T00:00:00Z",
+            "tests": [
+                {"id": "t1", "category": "C", "description": "D",
+                 "passed": False, "reason": "broken", "response": "nope", "latency_s": 1, "tokens": 0},
+            ],
+            "summary": {"total": 1, "passed": 0, "failed": 1, "errors": 0},
+        }
+        md = tc.to_markdown(results)
+        assert "NOT VIABLE" in md
+
+
+# ── Test Definitions ──────────────────────────────────────────────────
+
+class TestTestDefinitions:
+    def test_all_tests_have_validators(self):
+        for test in tc.TESTS:
+            assert callable(test["validate"]), f"{test['id']} missing validate"
+            assert "id" in test
+            assert "category" in test
+            assert "prompt" in test
+
+    def test_five_test_categories(self):
+        categories = {t["category"] for t in tc.TESTS}
+        assert len(categories) >= 4, f"Expected 4+ categories, got {categories}"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])