Pythonic task execution library for managing shell-oriented subprocesses and organizing executable Python code into CLI-invokable tasks
Overall
score
96%
{
"context": "This evaluation assesses the engineer's ability to use invoke's stream watching capabilities, specifically the Responder class from invoke.watchers, to automatically respond to interactive command prompts. The focus is on correct usage of pattern matching and auto-response mechanisms.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Imports Responder class",
"description": "Correctly imports the Responder class from invoke.watchers module",
"max_score": 10
},
{
"name": "Creates Responder instances",
"description": "Creates Responder instances with pattern and response parameters for both the confirmation and passphrase prompts",
"max_score": 20
},
{
"name": "Confirmation pattern matching",
"description": "Configures a Responder with a pattern that matches 'Do you want to continue? (yes/no):' (using regex or exact string)",
"max_score": 15
},
{
"name": "Confirmation response",
"description": "Configures the confirmation Responder to respond with 'yes\\n' (including newline)",
"max_score": 10
},
{
"name": "Passphrase pattern matching",
"description": "Configures a Responder with a pattern that matches 'Enter passphrase:' (using regex or exact string)",
"max_score": 15
},
{
"name": "Passphrase response",
"description": "Configures the passphrase Responder to respond with 'secret123\\n' (including newline)",
"max_score": 10
},
{
"name": "Watchers parameter usage",
"description": "Passes Responder instances to c.run() using the watchers parameter (as a list or single instance)",
"max_score": 15
},
{
"name": "Task decorator usage",
"description": "Both functions are properly decorated with @task decorator",
"max_score": 5
}
]
}Install with Tessl CLI
npx tessl i tessl/pypi-invokedocs
evals
scenario-1
scenario-2
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scenario-10