full-output-enforcement

Enforces complete code generation by banning placeholder patterns and truncation.

Updated Aug 15, 2025
One-click install
npx skills add https://github.com/yehezkieldio/topaz --skill full-output-enforcement-yehezkieldio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: full-output-enforcement
Source: https://github.com/yehezkieldio/topaz/tree/main/.agents/skills/full-output-enforcement
Command: npx skills add https://github.com/yehezkieldio/topaz --skill full-output-enforcement-yehezkieldio

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? LLMs often truncate long outputs, insert placeholder comments like "// rest of code", or skip deliverables to save tokens, leaving users with broken or incomplete code. This Skill overrides that default behavior so every requested file, function, or section is delivered in full. ## Core Features & Use Cases - Placeholder Ban: Hard-fails on patterns like // ..., // TODO, "for brevity", and skeleton-only outputs, forcing real runnable code. - Scope Locking: Counts the exact number of requested deliverables before generating, then cross-checks the output against that count. - Token-Limit Handling: When output approaches the token limit, it pauses at a clean breakpoint with a resumable marker instead of compressing or skipping content. - Use Case: Ask for a full 5-component React dashboard. Instead of receiving two components and "the rest follows the same pattern", you get all five fully implemented, or a clean pause marker you can resume from with "continue". ## Quick Start Apply the full-output-enforcement skill and generate the complete implementation of all requested files with no placeholders or omissions.

Frequently Asked Questions about full-output-enforcement

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I stop an LLM from truncating code output?▼

Apply output enforcement rules that ban placeholder patterns like "// rest of code" and require every requested deliverable to be generated in full. The skill counts expected deliverables upfront and cross-checks the response before finalizing.

How to handle token limits during long code generation?▼

Write at full quality up to a clean breakpoint such as the end of a function or file, then emit a pause marker stating progress. On "continue", resume exactly from that point with no recap or repetition.

What placeholder patterns should be banned in AI code generation?▼

Banned patterns include "// ...", "// TODO", "// implement here", "// similar to above", and prose like "for brevity" or "the rest follows the same pattern". These indicate omitted content and produce non-runnable output.

When should I not use full-output enforcement?▼

Avoid it for exploratory questions, quick snippets, or when you explicitly want a summary or skeleton. The enforcement treats every task as production-critical, which adds unnecessary length to casual requests.

Does output enforcement work with any LLM or framework?▼

Yes, it is a prompt-level instruction set with no code dependencies, so it works with any LLM that accepts system or skill instructions. It requires no scripts, libraries, or platform-specific setup.