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gh-yaleh-meta-cc-claude/skills/code-refactoring/knowledge/patterns-summary.json
2025-11-30 09:07:22 +08:00

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{
"pattern_count": 8,
"patterns": [
{
"name": "builder_map_decomposition",
"description": "\u2014 Map tool/command identifiers to factory functions to eliminate switch ladders and ease extension (evidence: MCP server Iteration 1)."
},
{
"name": "pipeline_config_struct",
"description": "\u2014 Gather shared parameters into immutable config structs so orchestration functions stay linear and testable (evidence: MCP server Iteration 1)."
},
{
"name": "helper_specialization",
"description": "\u2014 Push tracing/metrics/error branches into helpers to keep primary logic readable and reuse instrumentation (evidence: MCP server Iteration 1)."
},
{
"name": "jq_pipeline_segmentation",
"description": "\u2014 Treat JSONL parsing, jq execution, and serialization as independent helpers to confine failure domains (evidence: MCP server Iteration 2)."
},
{
"name": "automation_first_metrics",
"description": "\u2014 Bundle metrics capture in scripts/make targets so every iteration records complexity & coverage automatically (evidence: MCP server Iteration 2, CLI Iteration 3)."
},
{
"name": "documentation_templates",
"description": "\u2014 Use standardized iteration templates + generators to maintain BAIME completeness with minimal overhead (evidence: MCP server Iteration 3, CLI Iteration 3)."
},
{
"name": "conversation_turn_builder",
"description": "\u2014 Extract user/assistant maps and assemble turns through helper orchestration to control complexity in conversation analytics (evidence: CLI Iteration 4)."
},
{
"name": "prompt_outcome_analyzer",
"description": "\u2014 Split prompt outcome evaluation into dedicated helpers (confirmation, errors, deliverables, status) for predictable analytics (evidence: CLI Iteration 4)."
}
]
}