인터페이스는 현지화되어 있으며, Skill 소개와 설명 문서는 선택한 언어로 AI가 자동 번역합니다. 코드·명령어·경로·전문 용어는 원문을 유지하며 원작자 문서가 우선합니다.
Skills 둘러보기
생산성 및 협업 · SKILL.md

instruction_formatting

instruction_formatting

Render FLAN-style instruction examples with direct, exemplar, and chain-of-thought formatting controls.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: instruction_formatting description: Render FLAN-style instruction examples with direct, exemplar, and chain-of-thought formatting controls.

Instruction Formatting

Use this skill when building FLAN-style instruction-finetuning data, recovery fixtures, or tests that need prompt-target records. Do not use it to evaluate model outputs or to compose the full task mixture; it only formats individual examples.

Inputs

  • A task record with instruction, input, answer, mode, optional rationale, and optional exemplars.
  • mode must be direct or cot.

Outputs

  • prompt: user-visible instruction prompt.
  • target: supervised target text.
  • metadata: mode, exemplar count, and chain-of-thought flag.

Workflow

  1. Validate required fields and mode.
  2. Add exemplar blocks before the current input when provided.
  3. Render direct targets as the concise answer only.
  4. Render CoT targets as rationale plus Final answer: ....
  5. Keep rationales out of direct examples and out of prompts.

Validation

Run python tests/test_instruction_formatter.py or validate the tree with validate_skill_tree.py --run-tests.

Limitations

This skill does not choose task sampling weights and does not call a language model. It preserves the paper's formatting contract for downstream mixture, training, and proxy-evaluation modules.

저장한 Skills