Installs into .claude/skills of the current project.
Are you the author of Instruction Encoding Variants?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-instruction-encoding-variants)
---
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.
