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Design and scaffold evaluations comparing single-candidate Composer coding against adaptive Heavy Coder candidate teams.
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Based on SOC occupation classification
Keep coordinator and leaf context lean-batch reads, cap logs, use execute_code to filter-so swarms stay fast and within token limits.
Use at the start of non-trivial software tasks. Gather repo ground truth with batched reads and searches before planning or delegate_task.
Obey Plan 1A hook session phases so mutating tools, delegate_task sizing, and re-planning do not waste turns or trigger blocks.
Use when spawning delegate_task leaves for coding work. Pack self-contained goals and context so parallel Composer workers ship verifiable patches without coordinator chat history.
Require structured candidate-result JSON from swarm leaves so critique_candidates.py and synthesis run on evidence, not prose self-reports.
Enrich slim hook-injected delegate_tasks with touch map, failure excerpts, and verification commands so parallel leaves produce verifiable patches without coordinator chat history.
| name | heavy-coding-eval |
| description | Design and scaffold evaluations comparing single-candidate Composer coding against adaptive Heavy Coder candidate teams. |
| version | 0.1.0 |
| author | CodeGraphTheory |
| license | MIT |
Use this skill when planning or running Heavy Coder evaluations.
Scaffolded. Benchmark execution is not implemented.
candidate_widths), blind comparative critic, reasoning-model synthesis when available, same verifier.