full-output-enforcement

Enforces complete, unabridged code generation by banning placeholder patterns and truncation.

Updated Aug 26, 2026

Search Tags:#code generation #prompting #token limit #llm output #anti-truncation #placeholder ban #complete output

Ready to run

npx skills add https://github.com/Yjj0333/skills-manager-backup --skill full-output-enforcement-yjj0333

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: full-output-enforcement
Source: https://github.com/Yjj0333/skills-manager-backup/tree/main/full-output-enforcement
Command: npx skills add https://github.com/Yjj0333/skills-manager-backup --skill full-output-enforcement-yjj0333

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. This Skill eliminates those behaviors 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. - Scope Locking: Counts expected deliverables before generating and cross-checks the count before responding. - Clean Token-Limit Handling: Pauses at a clean breakpoint with a resume marker instead of compressing or skipping content. - Use Case: Ask for a full 5-component React dashboard and receive all 5 components completely implemented, with no omitted logic or "similar to above" shortcuts. ## 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 explicit output rules that ban placeholder patterns like "// rest of code" and require every requested deliverable to be generated in full. This Skill locks the deliverable count before generating and cross-checks it before responding.

How to handle token limits when generating long code files?▼

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 without recap or repetition.

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

Ban patterns like "// ...", "// TODO", "// implement here", "// similar to above", and prose such as "for brevity" or "the rest follows the same pattern". These indicate omitted content and count as hard failures.

When should I not use full-output enforcement?▼

Avoid it for exploratory questions, quick prototypes, or when the user explicitly asks for a summary or skeleton. Forcing exhaustive output in those cases wastes tokens and slows iteration.