{"results":{"result":{"added-files":{"code-health":0.0,"old-code-health":0.0,"files":[]},"external-review-url":"https://github.com/abhimehro/ctrld-sync/pull/738","old-code-health":1.6624201552574078,"modified-files":{"code-health":1.8818770287044986,"old-code-health":1.6624201552574078,"files":[{"file":"main.py","loc":2288,"old-loc":2492,"code-health":1.8818770287044986,"old-code-health":1.6624201552574078}]},"removed-files":{"code-health":0.0,"old-code-health":0.0,"files":[]},"external-review-id":"738","analysis-time":"2026-04-24T23:32:26Z","negative-impact-count":0,"suppressions":{"number-of-types":0,"number-of-files-touched":0,"findings":[]},"affected-hotspots":1,"commits":["9f749e82226e43654a5554a4025b3fd8c29ff9e7","a61a07a5dd29c2fabcab52c0b71ea373eca42040"],"is-negative-review":false,"negative-findings":{"number-of-types":0,"number-of-files-touched":0,"findings":[]},"positive-impact-count":24,"repo":"ctrld-sync","code-health":1.8818770287044986,"version":"3.0","authors":["google-labs-jules[bot]"],"directives":{"added":[],"removed":[]},"positive-findings":{"number-of-types":7,"number-of-files-touched":1,"findings":[{"name":"Lines of Code in a Single File","file":"main.py","change-type":"improved","change-level":"improvement","is-hotspot?":true,"why-it-occurs":"This module has 1951 lines of code (comments stripped away). This puts the module at risk of evolving into a Brain Class. Brain Classes are problematic since changes become more complex over time, harder to test, and challenging to refactor. Act now to prevent future maintenance issues.","how-to-fix":"Look for opportunities to modularize the design. This is done by identifying groups of functions that represent different responsibilities and/or operate on different data. Once you have identified the different responsibilities, then use refactorings like [EXTRACT CLASS](https://refactoring.com/catalog/extractClass.html).","what-changed":"The lines of code decreases from 2165 to 1951, improve code health by reducing it to 600"},{"method":"sync_profile","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2144,"what-changed":"sync_profile decreases in cyclomatic complexity from 35 to 34, threshold = 9","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"improved"},{"method":"verify_access_and_get_folders","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1464,"what-changed":"verify_access_and_get_folders decreases in cyclomatic complexity from 21 to 19, threshold = 9","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"improved"},{"method":"validate_folder_data","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1105,"what-changed":"validate_folder_data decreases in cyclomatic complexity from 25 to 17, threshold = 9","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"improved"},{"method":"warm_up_cache","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1694,"what-changed":"warm_up_cache decreases in cyclomatic complexity from 11 to 10, threshold = 9","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"improved"},{"method":"prompt_for_interactive_restart","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2374,"what-changed":"prompt_for_interactive_restart decreases in cyclomatic complexity from 12 to 9, threshold = 9","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"improved"},{"method":"push_rules","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2135,"what-changed":"push_rules is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"create_folder","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2033,"what-changed":"create_folder is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"print_summary_table","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2678,"what-changed":"print_summary_table is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"_is_safe_ip","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1073,"what-changed":"_is_safe_ip is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"print_success_message","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2748,"what-changed":"print_success_message is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"list_existing_folders","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1678,"what-changed":"list_existing_folders is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"check_api_access","why-it-occurs":"A Complex Method has a high cyclomatic complexity. The recommended threshold for the Python language is a cyclomatic complexity lower than 9.","name":"Complex Method","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1633,"what-changed":"check_api_access is no longer above the threshold for cyclomatic complexity","how-to-fix":"There are many reasons for Complex Method. Sometimes, another design approach is beneficial such as a) modeling state using an explicit state machine rather than conditionals, or b) using table lookup rather than long chains of logic. In other scenarios, the function can be split using [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html). Just make sure you extract natural and cohesive functions. Complex Methods can also be addressed by identifying complex conditional expressions and then using the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring.","change-type":"fixed"},{"method":"_is_valid_rule_list","why-it-occurs":"A complex conditional is an expression inside a branch such as an <code>if</code>-statmeent which consists of multiple, logical operations. Example: <code>if (x.started() && y.running())</code>.Complex conditionals make the code even harder to read, and contribute to the Complex Method code smell. Encapsulate them.","name":"Complex Conditional","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1306,"what-changed":"_is_valid_rule_list no longer has a complex conditional","how-to-fix":"Apply the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring so that the complex conditional is encapsulated in a separate function with a good name that captures the business rule. Optionally, for simple expressions, introduce a new variable which holds the result of the complex conditional.","change-type":"fixed"},{"method":"create_folder","why-it-occurs":"A complex conditional is an expression inside a branch such as an <code>if</code>-statmeent which consists of multiple, logical operations. Example: <code>if (x.started() && y.running())</code>.Complex conditionals make the code even harder to read, and contribute to the Complex Method code smell. Encapsulate them.","name":"Complex Conditional","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2052,"what-changed":"create_folder no longer has a complex conditional","how-to-fix":"Apply the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring so that the complex conditional is encapsulated in a separate function with a good name that captures the business rule. Optionally, for simple expressions, introduce a new variable which holds the result of the complex conditional.","change-type":"fixed"},{"method":"push_rules","why-it-occurs":"A complex conditional is an expression inside a branch such as an <code>if</code>-statmeent which consists of multiple, logical operations. Example: <code>if (x.started() && y.running())</code>.Complex conditionals make the code even harder to read, and contribute to the Complex Method code smell. Encapsulate them.","name":"Complex Conditional","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2252,"what-changed":"push_rules no longer has a complex conditional","how-to-fix":"Apply the [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring so that the complex conditional is encapsulated in a separate function with a good name that captures the business rule. Optionally, for simple expressions, introduce a new variable which holds the result of the complex conditional.","change-type":"fixed"},{"method":"sync_profile","why-it-occurs":"A Bumpy Road is a function that contains multiple chunks of nested conditional logic inside the same function. The deeper the nesting and the more bumps, the lower the code health.\n\nA bumpy code road represents a lack of encapsulation which becomes an obstacle to comprehension. In imperative languages there’s also an increased risk for feature entanglement, which leads to complex state management. CodeScene considers the following rules for the code health impact: 1) The deeper the nested conditional logic of each bump, the higher the tax on our working memory. 2) The more bumps inside a function, the more expensive it is to refactor as each bump represents a missing abstraction. 3) The larger each bump – that is, the more lines of code it spans – the harder it is to build up a mental model of the function. The nesting depth for what is considered a bump is  levels of conditionals.","name":"Bumpy Road Ahead","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2144,"what-changed":"sync_profile decreases from 7 to 6 logical blocks with deeply nested code, threshold is 2 blocks per function","how-to-fix":"Bumpy Road implementations indicate a lack of encapsulation. Check out the detailed description of the [Bumpy Road code health issue](https://codescene.com/blog/bumpy-road-code-complexity-in-context/).\n\nA Bumpy Road often suggests that the function/method does too many things. The first refactoring step is to identify the different possible responsibilities of the function. Consider extracting those responsibilities into smaller, cohesive, and well-named functions. The [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html) refactoring is the primary response.","change-type":"improved"},{"method":"validate_folder_data","why-it-occurs":"A Bumpy Road is a function that contains multiple chunks of nested conditional logic inside the same function. The deeper the nesting and the more bumps, the lower the code health.\n\nA bumpy code road represents a lack of encapsulation which becomes an obstacle to comprehension. In imperative languages there’s also an increased risk for feature entanglement, which leads to complex state management. CodeScene considers the following rules for the code health impact: 1) The deeper the nested conditional logic of each bump, the higher the tax on our working memory. 2) The more bumps inside a function, the more expensive it is to refactor as each bump represents a missing abstraction. 3) The larger each bump – that is, the more lines of code it spans – the harder it is to build up a mental model of the function. The nesting depth for what is considered a bump is  levels of conditionals.","name":"Bumpy Road Ahead","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1105,"what-changed":"validate_folder_data decreases from 6 to 4 logical blocks with deeply nested code, threshold is 2 blocks per function","how-to-fix":"Bumpy Road implementations indicate a lack of encapsulation. Check out the detailed description of the [Bumpy Road code health issue](https://codescene.com/blog/bumpy-road-code-complexity-in-context/).\n\nA Bumpy Road often suggests that the function/method does too many things. The first refactoring step is to identify the different possible responsibilities of the function. Consider extracting those responsibilities into smaller, cohesive, and well-named functions. The [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html) refactoring is the primary response.","change-type":"improved"},{"method":"push_rules","why-it-occurs":"A Bumpy Road is a function that contains multiple chunks of nested conditional logic inside the same function. The deeper the nesting and the more bumps, the lower the code health.\n\nA bumpy code road represents a lack of encapsulation which becomes an obstacle to comprehension. In imperative languages there’s also an increased risk for feature entanglement, which leads to complex state management. CodeScene considers the following rules for the code health impact: 1) The deeper the nested conditional logic of each bump, the higher the tax on our working memory. 2) The more bumps inside a function, the more expensive it is to refactor as each bump represents a missing abstraction. 3) The larger each bump – that is, the more lines of code it spans – the harder it is to build up a mental model of the function. The nesting depth for what is considered a bump is  levels of conditionals.","name":"Bumpy Road Ahead","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2135,"what-changed":"push_rules is no longer above the threshold for logical blocks with deeply nested code","how-to-fix":"Bumpy Road implementations indicate a lack of encapsulation. Check out the detailed description of the [Bumpy Road code health issue](https://codescene.com/blog/bumpy-road-code-complexity-in-context/).\n\nA Bumpy Road often suggests that the function/method does too many things. The first refactoring step is to identify the different possible responsibilities of the function. Consider extracting those responsibilities into smaller, cohesive, and well-named functions. The [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html) refactoring is the primary response.","change-type":"fixed"},{"method":"create_folder","why-it-occurs":"A Bumpy Road is a function that contains multiple chunks of nested conditional logic inside the same function. The deeper the nesting and the more bumps, the lower the code health.\n\nA bumpy code road represents a lack of encapsulation which becomes an obstacle to comprehension. In imperative languages there’s also an increased risk for feature entanglement, which leads to complex state management. CodeScene considers the following rules for the code health impact: 1) The deeper the nested conditional logic of each bump, the higher the tax on our working memory. 2) The more bumps inside a function, the more expensive it is to refactor as each bump represents a missing abstraction. 3) The larger each bump – that is, the more lines of code it spans – the harder it is to build up a mental model of the function. The nesting depth for what is considered a bump is  levels of conditionals.","name":"Bumpy Road Ahead","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2033,"what-changed":"create_folder is no longer above the threshold for logical blocks with deeply nested code","how-to-fix":"Bumpy Road implementations indicate a lack of encapsulation. Check out the detailed description of the [Bumpy Road code health issue](https://codescene.com/blog/bumpy-road-code-complexity-in-context/).\n\nA Bumpy Road often suggests that the function/method does too many things. The first refactoring step is to identify the different possible responsibilities of the function. Consider extracting those responsibilities into smaller, cohesive, and well-named functions. The [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html) refactoring is the primary response.","change-type":"fixed"},{"name":"Overall Code Complexity","file":"main.py","change-type":"improved","change-level":"improvement","is-hotspot?":true,"why-it-occurs":"Overall Code Complexity is measured by the mean cyclomatic complexity across all functions in the file. The lower the number, the better.\n\nCyclomatic complexity is a function level metric that measures the number of logical branches (if-else, loops, etc.). Cyclomatic complexity is a rough complexity measure, but useful as a way of estimating the minimum number of unit tests you would need. As such, prefer functions with low cyclomatic complexity (2-3 branches).","how-to-fix":"You address the overall cyclomatic complexity by a) modularizing the code, and b) abstract away the complexity. Let's look at some examples:\n\nModularizing the Code: Do an X-Ray and inspect the local hotspots. Are there any complex conditional expressions? If yes, then do a [DECOMPOSE CONDITIONAL](https://refactoring.com/catalog/decomposeConditional.html) refactoring. Extract the conditional logic into a separate function and put a good name on that function. This clarifies the intent and makes the original function easier to read. Repeat until all complex conditional expressions have been simplified.\n\n","what-changed":"The mean cyclomatic complexity decreases from 10.17 to 9.67, threshold = 4"},{"method":"validate_folder_data","why-it-occurs":"Deep nested logic means that you have control structures like if-statements or loops inside other control structures. Deep nested logic increases the cognitive load on the programmer reading the code. The human working memory has a maximum capacity of 3-4 items; beyond that threshold, we struggle with keeping things in our head. Consequently, deep nested logic has a strong correlation to defects and accounts for roughly 20% of all programming mistakes.\n\nCodeScene measures the maximum nesting depth inside each function. The deeper the nesting, the lower the code health. The threshold for the Python language is 5 levels of nesting.","name":"Deep, Nested Complexity","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":1105,"what-changed":"validate_folder_data decreases in nested complexity depth from 6 to 5, threshold = 4","how-to-fix":"Occassionally, it's possible to get rid of the nested logic by [Replacing Conditionals with Guard Clauses](https://refactoring.com/catalog/replaceNestedConditionalWithGuardClauses.html).\n\nAnother viable strategy is to identify smaller building blocks inside the nested chunks of logic and extract those responsibilities into smaller, cohesive, and well-named functions. The [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html) refactoring explains the steps.","change-type":"improved"},{"method":"create_folder","why-it-occurs":"Deep nested logic means that you have control structures like if-statements or loops inside other control structures. Deep nested logic increases the cognitive load on the programmer reading the code. The human working memory has a maximum capacity of 3-4 items; beyond that threshold, we struggle with keeping things in our head. Consequently, deep nested logic has a strong correlation to defects and accounts for roughly 20% of all programming mistakes.\n\nCodeScene measures the maximum nesting depth inside each function. The deeper the nesting, the lower the code health. The threshold for the Python language is  levels of nesting.","name":"Deep, Nested Complexity","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2033,"what-changed":"create_folder is no longer above the threshold for nested complexity depth","how-to-fix":"Occassionally, it's possible to get rid of the nested logic by [Replacing Conditionals with Guard Clauses](https://refactoring.com/catalog/replaceNestedConditionalWithGuardClauses.html).\n\nAnother viable strategy is to identify smaller building blocks inside the nested chunks of logic and extract those responsibilities into smaller, cohesive, and well-named functions. The [EXTRACT FUNCTION](https://refactoring.com/catalog/extractFunction.html) refactoring explains the steps.","change-type":"fixed"},{"method":"make_col_separator","why-it-occurs":"Functions with many arguments indicate either a) low cohesion where the function has too many responsibilities, or b) a missing abstraction that encapsulates those arguments.\n\nThe threshold for the Python language is 4 function arguments.","name":"Excess Number of Function Arguments","file":"main.py","change-level":"improvement","is-hotspot?":true,"line":2830,"what-changed":"make_col_separator is no longer above the threshold for number of arguments","how-to-fix":"Start by investigating the responsibilities of the function. Make sure it doesn't do too many things, in which case it should be split into smaller and more cohesive functions. Consider the refactoring [INTRODUCE PARAMETER OBJECT](https://refactoring.com/catalog/introduceParameterObject.html) to encapsulate arguments that refer to the same logical concept.","change-type":"fixed"}]},"notices":{"number-of-types":0,"number-of-files-touched":0,"findings":[]},"external-review-provider":"GitHub"},"analysistime":"2026-04-24T23:32:26.000Z","project-name":"abhimehro","repository":"https://github.com/abhimehro/ctrld-sync.git"}}