Standard Multimodal Prompt Grammar Specification

Role: Principal Multimodal Prompt Engineer and Core Systems Documentation Lead

Context

• Target Foundation Model: {{foundation_model}}
• Supported Modalities: {{target_modalities}}
• Prompt Syntax Dialect: {{syntax_dialect}}
• Core Model Parameters: {{supported_parameters}}
• Specification Version: {{version_number}}
• Maximum Context Token Limit: {{token_budget}}

Task

Draft a formal technical prompt grammar specification for {{foundation_model}} that standardizes token weighting, parameter injection, negative prompt parsing, and multimodal reference syntax into a production-ready engineering reference document.

Method

1. Define the top-level formal grammar syntax using the conventions of {{syntax_dialect}}.
2. Document the structural taxonomy for ordering semantic prefixes, scene descriptors, style tokens, and technical switches within {{token_budget}}.
3. Establish exact mathematical notation and syntax rules for token emphasis, attention weighting, and token blending.
4. Formalize the integration mechanics for multimodal inputs specified in {{target_modalities}} such as image-to-image weights and depth masks.
5. Specify supported runtime parameters including {{supported_parameters}}, declaring valid ranges, step sizes, and default fallbacks.
6. Detail negative prompt processing logic and token collision resolution.
7. Provide canonical valid and invalid code-style prompt examples illustrating boundary conditions.

Constraints

• MUST define explicit error handling behaviors for malformed tokens or syntax boundary violations.
• MUST use clear tabular layouts for all parameter ranges, data types, and default values.
• MUST NOT leave any token modifier syntax ambiguous or undefined.
• Keep technical prose concise, authoritative, and direct.

Output format

1. Header Block (Specification Title, Version {{version_number}}, Engine Target {{foundation_model}})
2. Lexical & Grammar Architecture (EBNF or standard notation)
3. Parameter Data Contract (Markdown table: Name, Type, Range, Default, Description)
4. Multimodal Token Ingestion Rules (Targeting {{target_modalities}})
5. Validated Reference Examples (3 valid specifications, 2 invalid test cases with error states)

Self-review

• Ensure all variables ({{foundation_model}}, {{syntax_dialect}}, {{supported_parameters}}, etc.) are mapped correctly.
• Verify all parameter ranges and step increments contain deterministic boundary limits.
• Confirm notation syntax adheres to standard technical spec writing without narrative filler.