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效率与协作 · SKILL.md

instruction_encoding_variants

instruction_encoding_variants

【效率与协作】Render Natural Instructions task records into paper-faithful instruction encoding variants for text-to-text models.

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技能说明

GitHub

name: instruction_encoding_variants description: Render Natural Instructions task records into paper-faithful instruction encoding variants for text-to-text models.

Instruction Encoding Variants

Use this skill when a recovery harness needs the exact style of textual model input compared in the paper. Do not include the held-out reference answer for the current instance in the encoding.

Inputs

  • A normalized instruction task record.
  • Current instance input text.
  • Variant: no_instruction, prompt, prompt_definition, positive_examples, prompt_definition_positive_examples, or full_instruction.

Outputs

  • Encoded text ending with output:.
  • Included field names for audit logs.

Workflow

  1. Choose the variant based on the ablation being tested.
  2. Render selected fields in a stable order: definition, prompt, things to avoid, emphasis, examples, current input.
  3. Label positive and negative examples explicitly.
  4. Append only the current input and an empty output slot.
  5. Pass the encoding to a model or reduced proxy scorer.

Validation

Run python tests/test_instruction_encoding_variants.py or validate with validate_skill_tree.py --run-tests.

Limitations

This skill does not truncate to BART’s maximum sequence length. Callers running full models must apply model-specific token limits.

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