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- Decision-equivalence rules map completed `Or` values identically. Decision-to-optimization rules own their feasibility/threshold map; reject target configurations that do not certify YES instead of returning an invalid source witness. Optimization rules decode optimal witnesses and evaluate the source; register a value map only when mathematically defined. Counting and universal rules map completed folds without witnesses. Follow [result mappings](../docs/src/design.md#result-mappings); no mandatory rule-category tags.
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- Decode only the reduction's defined mathematical mapping. Reject malformed structure with `ExtractionError`; never panic, truncate, clamp, invent defaults, or add recovery branches. Explicit mathematical alternatives and sentinels are allowed. Test successful decoding and every rejected representation.
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- CLI-facing dynamic formatting uses aggregate wrapper names directly (for example `Max(2)`, `Min(None)`, `Or(true)`, or `Sum(56)`)
let output = McpServer::new().create_problem_inner("MixedChinesePostman/i64",&serde_json::json!({"graph":[[0,0]],"arcs":[[0,0]],"num_vertices":1,"edge_weights":[3],"arc_weights":[2]})).unwrap();
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let json: serde_json::Value = serde_json::from_str(&output).unwrap();
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let problem: problemreductions::models::graph::MixedChinesePostman<i64> =
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