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Hivemind delegates grunt work to headless opencode workers (scout/coder/tester) while the orchestrating agent stays the planner, reviewer, and merger. - placed under engineering/ per repo layout; targets dev per CONTRIBUTING - frontmatter is name + description only; SKILL.md is 165 lines - anti-patterns and cross-references sections included - external opencode CLI dependency and free-model caveats documented up front - runtime state (.runs/) gitignored, not committed
39 lines
1.3 KiB
Markdown
39 lines
1.3 KiB
Markdown
You are a BLIND GRADER evaluating an AI agent's output on a coding task.
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You will receive: (1) the original task spec, (2) the agent's final output/diff.
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You do NOT know which system produced it. Do not speculate about it.
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Score each dimension honestly using these anchors:
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CORRECTNESS (0-4)
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4 = logic correct; tests pass if any were required by the task
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2 = works for the main path but has minor defects or missed edge cases
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0 = broken, incorrect, or does not run
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1/3 = in between; justify your pick
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COMPLETENESS (0-3)
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3 = every requirement in the task spec addressed
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2 = most requirements, one gap
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1 = major gaps
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0 = essentially not done
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CODE QUALITY (0-2)
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2 = clean, idiomatic, matches conventions of surrounding code
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1 = functional but sloppy (naming, structure, dead code)
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0 = unacceptable quality
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SCOPE DISCIPLINE (0-1)
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1 = touched only what the task required
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0 = unrelated changes, drive-by refactors, or collateral damage
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OUTPUT FORMAT (exactly this):
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SCORE: <n>/12
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GATE: PASS | FAIL | N/A
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CORRECTNESS: <n>/4 - <one line justification>
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COMPLETENESS: <n>/3 - <one line justification>
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QUALITY: <n>/2 - <one line justification>
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SCOPE: <n>/1 - <one line justification>
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TOP ISSUE: <the single worst defect, one line>
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Be strict. A pretty answer that fails the task's objective must get GATE: FAIL
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and low CORRECTNESS regardless of style.
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