Diagnose Haskell performance and strictness issues using GHC profiling and Core inspection.
npx skills add https://github.com/kaynetik/skills --skill practical-haskell
Please help me install this Agent Skill. Skill: practical-haskell Source: https://github.com/kaynetik/skills/tree/main/practical-haskell Command: npx skills add https://github.com/kaynetik/skills --skill practical-haskell
Helps diagnose and remediate Haskell performance, memory, and evaluation-order issues by aligning code with GHC optimization behavior and profiling evidence. It is focused on eliminating space leaks, improving strictness where appropriate, enabling fusion-friendly pipelines, and guiding pragmatic use of pragmas and newtypes.
Analyze the provided Haskell module using GHC profiling and simplified Core output and recommend concrete strictness, fusion, and specialization changes to reduce allocations and improve performance.
High-intent search queries and answers about installing and using this skill.
To fix a Haskell space leak from thunk buildup, apply strict fields, bang patterns, and foldl' to force evaluation and prevent deferred thunks from accumulating in memory.
Reading GHC simplified Core from -ddump-simpl output involves inspecting the optimized intermediate code to confirm that strictness analysis, worker/wrapper transformations, and fusion have successfully eliminated allocation overhead.
The best way to reduce Haskell allocations during profiling is to interpret profiler output to locate hotspots, then apply UNPACK pragmas and fusion-friendly pipelines to minimize intermediate data structures.
Use INLINE, INLINABLE, or SPECIALIZE pragmas in GHC when Core inspection shows dictionary or allocation overhead, enabling worker/wrapper transformations to eliminate typeclass indirection and improve throughput.
GHC fusion optimization works with strict fold pipelines when using foldl' and appropriate strictness annotations, allowing list operations to be optimized away while preventing space leaks from deferred evaluation.
High Haskell memory usage despite profiling often indicates hidden space leaks from lazy evaluation, requiring strictness analysis, strict data fields, and foldl' usage to eliminate thunk accumulation and reduce heap footprint.
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copyleftdevApply Simon Peyton Jones' heuristics for writing performant Haskell code.
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