tessl install tessl/pypi-crosshair-tool@0.0.0Analyze Python code for correctness using symbolic execution and SMT solving to automatically find counterexamples for functions with type annotations and contracts.
Agent Success
Agent success rate when using this tile
86%
Improvement
Agent success rate improvement when using this tile compared to baseline
1.25x
Baseline
Agent success rate without this tile
69%
{
"context": "This criteria evaluates how well the engineer uses CrossHair's symbolic execution and search capabilities to implement constraint validation and optimization. The focus is on proper usage of CrossHair's search APIs, symbolic value creation, and constraint solving features.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Symbolic value creation",
"description": "Uses proxy_for_type() or similar CrossHair APIs to create symbolic values for searching the configuration space in find_optimal_config",
"max_score": 25
},
{
"name": "Constraint implementation",
"description": "Properly implements all five constraints in validate_server_config using conditional logic that raises ValueError with descriptive messages",
"max_score": 20
},
{
"name": "Search command usage",
"description": "Uses crosshair search command or programmatic search APIs (like StateSpace, choose_possible, or realize) to find valid configurations",
"max_score": 25
},
{
"name": "Optimization strategy",
"description": "Implements logic in find_optimal_config that maximizes worker_threads while satisfying constraints, either through iterative search or scoring functions",
"max_score": 20
},
{
"name": "Integration completeness",
"description": "Correctly integrates CrossHair into the workflow with appropriate imports (from crosshair.core import proxy_for_type, realize, or similar) and proper function signatures matching the API",
"max_score": 10
}
]
}