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
887 B
887 B
OfficeQA Skill
Retrieval Discipline
- Start by narrowing to the most likely candidate file before reading long passages.
- Prefer targeted search terms that name the exact entity, period, measure, or table concept from the question.
- After a promising match, read only a small surrounding span and verify it matches the requested year, basis, and unit.
Evidence Discipline
- Extract the exact value from the retrieved text before doing any arithmetic.
- Keep track of each operand's period, unit, and semantic role so nearby proxy values are not mixed in.
- If the question asks for a transformed or derived quantity, compute only after confirming every operand.
Final Answer Discipline
- Return the final answer only after one last consistency check against the retrieved evidence.
- Copy the final answer from a checked value, not from an unverified intermediate guess.