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name: llava_conversation_prompting description: Format LLaVA-style multimodal prompts with image tokens, role boundaries, and answer-leakage checks.

LLaVA Conversation Prompting

Use this skill when preparing visual-instruction examples for training, inference, or recovery checks that need LLaVA-like Human/Assistant turn boundaries. Do not use it for final answer scoring; scoring belongs to an evaluation skill.

Inputs

• Instruction item with human_prompt and optional assistant_answer.
• Image token placeholder such as <image>.
• Separator policy, defaulting to `

` role separators.

Outputs

A prompt record containing user_prompt, optional training_prompt, and metadata that states whether the assistant answer was withheld from the user side.

Workflow

1. Prefix the human instruction with the image token.
2. Encode explicit Human and Assistant roles.
3. Keep the answer out of user_prompt; include it only in training_prompt when requested.
4. Return metadata suitable for generated-skill invocation logs.

Validation

Run the included tests or validate_skill_tree.py --run-tests.

Limitations

The formatter does not tokenize with Vicuna or load model weights; it preserves prompt contracts for bounded recovery.