pytest-aitest - Test Report

🤖AI Analysis

🎯 Executive Summary

Metric	Value
Best Configuration	🏆 model-gpt-5.2
Pass Rate	4/4 tests (100%)
Total Cost	$0.297 (gpt-5.2: $0.173, claude-opus-4.5: $0.253)
Recommendation	🟢 Deploy gpt-5.2

Verdict: Both agents passed all tests, but gpt-5.2 delivered more production-ready code (validation, logging, CLI support) at a lower cost than claude-opus-4.5.

Configuration Scorecard

Agent	Pass Rate	Cost	Avg Duration	Tool Use	Verdict
model-gpt-5.2	2/2 (100%)	$0.173	26.5s	create, view, glob, grep, powershell	🏆 Best
model-claude-opus-4.5	2/2 (100%)	$0.253	10.9s	create	✅ Correct but pricier

✅ Results Matrix

Test	gpt-5.2	claude-opus-4.5	Notes
Create Fibonacci function	✅	✅	Both correct, 0-indexed
JSON parser with error handling	✅	✅	gpt-5.2 more robust

🤖 Model Comparison

Capability	gpt-5.2	claude-opus-4.5
Correctness	✅	✅
Error handling depth	✅ Strong	⚠️ Basic
Input validation	✅ Yes	❌ No
Logging / defaults	✅ Yes	❌ No
CLI usability	✅ Included	❌ None
Tool utilization	⚠️ Heavy	✅ Minimal
Cost efficiency	🏆 Better	❌ Higher

gpt-5.2

Verdict: Best choice for production-oriented coding agents where robustness and extensibility matter.

Strengths: - Adds input validation (TypeError, ValueError) - Graceful error handling with defaults and logging - Self-verifies output via CLI execution - Uses tools to confirm assumptions (tests, workspace scan)

Weaknesses: - Slightly slower - Extra tool calls may be unnecessary for trivial tasks

claude-opus-4.5

Verdict: Good for fast, minimal implementations when simplicity is preferred over robustness.

Strengths: - Very fast execution - Concise, readable code - Minimal tool usage

Weaknesses: - No input validation - Error handling limited to print statements - No extensibility hooks (logging, defaults, CLI)

🔧 Tool Usage

Tool Proficiency Matrix

Tool	gpt-5.2	claude-opus-4.5	Assessment
create	✅	✅	Required
view	✅	❌	Useful for verification
glob / grep	⚠️	❌	Likely unnecessary
powershell	✅	❌	Good self-check

Observation: gpt-5.2 tends to over-explore the workspace. Claude relies on prompt confidence and skips verification.

💡 Optimizations

Priority	Change	Expected Impact
🟡 Recommended	Reduce exploratory `glob/grep` for simple tasks	⬇️ ~10–15% cost
🟢 Nice to have	Add optional validation to Claude instructions	⬆️ Code robustness

Details: 1. Reduce workspace scanning (gpt-5.2) - Current: Multiple glob/grep calls even when no tests exist - Change: Add instruction:
Only inspect the workspace if tests or specifications are explicitly mentioned. - Impact: Faster execution, lower cost, same correctness

✅ Final Recommendation

Deploy model-gpt-5.2 as the default coding agent.
It matches Claude’s correctness while delivering better engineering quality at a lower cost, making it the stronger baseline for real-world coding tasks.

🏆 Agent Leaderboard

	Agent	Tests	Pass Rate	Cost	Duration
🥇	model-gpt-5.2	1/1	100%	$0.0716	27.4s
🥈	model-gpt-5.2	1/1	100%	$0.1014	25.5s
🥉	model-claude-opus-4.5	1/1	100%	$0.1245	10.8s
4	model-claude-opus-4.5	1/1	100%	$0.1282	11.1s

Compare:(Click to swap agents)

model-gpt-5.2100%model-gpt-5.2100%model-claude-opus-4.5100%model-claude-opus-4.5100%

📋 Test Results

4 / 4 tests

🔗Compare models on the same task.(2 tests)

1/1

▼

✅Each model should create a working function.

Total 0 tok·Total $0.1014·Δ +0%·Δ +0%·Δ +0%

model-gpt-5.2:—

model-gpt-5.2:✅25.5s

model-gpt-5.2

No result for this agent

model-gpt-5.2

passed

25.51s

duration

16

turns

9

tools

0

tokens

$0.1014

cost

📊Sequence

sequenceDiagram participant User participant Agent participant Tools User->>Agent: "Create fibonacci.py with a function fibonacci(n) that returns the nth Fibonacci " Agent->>Tools: "report_intent({'intent': 'Inspecting tests'})" Agent->>Tools: "glob({'pattern': '**/*', 'path': 'C:\\Users\\stbrnner\\AppData\\L)" Agent->>Tools: "grep({'pattern': 'fibonacci', 'path': 'C:\\Users\\stbrnner\\AppDa)" Agent->>Tools: "report_intent({'intent': 'Creating fibonacci module'})" Agent->>Tools: "create({'path': 'C:\\Users\\stbrnner\\AppData\\Local\\Temp\\pytest-)" Agent->>Tools: "view({'path': 'C:\\Users\\stbrnner\\AppData\\Local\\Temp\\pytest-)" Agent->>Tools: "report_intent({'intent': 'Verifying file creation'})" Agent->>Tools: "view({'path': 'C:\\Users\\stbrnner\\AppData\\Local\\Temp\\pytest-)" Agent->>Tools: "powershell({'command': 'python -c 'from fibonacci import fibonacci; pri)" Agent->>User: "Created `fibonacci.py` with a `fibonacci(n)` function (0-indexed: `fibonacci(0)=" Agent->>User: "Created `fibonacci.py` with a `fibonacci(n)` function (0-indexed: `fibonacci(0)="

🔧Tool Calls

✅report_intent

✅glob

✅grep

✅report_intent

✅create

✅view

✅report_intent

✅view

✅powershell

💬Response

Created `fibonacci.py` with a `fibonacci(n)` function (0-indexed: `fibonacci(0)=0`, `fibonacci(1)=1`) using an iterative implementation and basic input validation.

✅Each model should produce code with proper error handling.

Total 0 tok·Total $0.0716·Δ +0%·Δ +0%·Δ +0%

model-gpt-5.2:✅27.4s

model-gpt-5.2:—

model-gpt-5.2

passed

27.41s

duration

12

turns

7

tools

0

tokens

$0.0716

cost

📊Sequence

sequenceDiagram participant User participant Agent participant Tools User->>Agent: "Create a file parser.py that reads a JSON file and returns its contents. Handle " Agent->>Tools: "report_intent({'intent': 'Inspecting workspace'})" Agent->>Tools: "glob({'pattern': '**/*', 'path': '.'})" Agent->>Tools: "glob({'pattern': '**/*.py', 'path': '.'})" Agent->>Tools: "glob({'pattern': '**/test*.py', 'path': '.'})" Agent->>Tools: "report_intent({'intent': 'Creating JSON parser'})" Agent->>Tools: "create({'path': 'C:\\Users\\stbrnner\\AppData\\Local\\Temp\\pytest-)" Agent->>Tools: "powershell({'command': 'python -m py_compile .\\parser.py', 'descriptio)" Agent->>User: "Created `parser.py` with a `read_json_file(path, default=None, logger=None)` fun" Agent->>User: "Created `parser.py` with a `read_json_file(path, default=None, logger=None)` fun"

🔧Tool Calls

✅report_intent

✅glob

✅report_intent

✅create

✅powershell

💬Response

Created `parser.py` with a `read_json_file(path, default=None, logger=None)` function that reads and returns parsed JSON content, returning `default` on `FileNotFoundError` or `json.JSONDecodeError` (optionally logging a warning).

model-gpt-5.2

No result for this agent