CharlesYang030
244e346b83
- Skill optimization framework with training loop analogy - 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen) - WebUI for browser-based training control - Pluggable architecture for extending benchmarks and backends
16 lines
887 B
Markdown
16 lines
887 B
Markdown
# OfficeQA Skill
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## Retrieval Discipline
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- Start by narrowing to the most likely candidate file before reading long passages.
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- Prefer targeted search terms that name the exact entity, period, measure, or table concept from the question.
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- After a promising match, read only a small surrounding span and verify it matches the requested year, basis, and unit.
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## Evidence Discipline
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- Extract the exact value from the retrieved text before doing any arithmetic.
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- Keep track of each operand's period, unit, and semantic role so nearby proxy values are not mixed in.
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- If the question asks for a transformed or derived quantity, compute only after confirming every operand.
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## Final Answer Discipline
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- Return the final answer only after one last consistency check against the retrieved evidence.
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- Copy the final answer from a checked value, not from an unverified intermediate guess.
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