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full-output-enforcement

Enforces complete, unabridged LLM output by banning placeholder patterns and truncation.

Updated Jul 16, 2026
Search Tags:#code generation#completeness#llm output#placeholder detection#prompt instructions#anti-truncation
One-click install
npx skills add https://github.com/optimaxin/Tredev_Gems --skill full-output-enforcement-optimaxin
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: full-output-enforcement
Source: https://github.com/optimaxin/Tredev_Gems/tree/main/agent/skills/full-output-enforcement
Command: npx skills add https://github.com/optimaxin/Tredev_Gems --skill full-output-enforcement-optimaxin

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? LLMs often truncate long responses, insert placeholder comments like "// rest of code", or skip deliverables to save tokens, leaving users with incomplete code and partial answers that require manual follow-up. ## Core Features & Use Cases - Placeholder Ban: Hard-fails on patterns like "// ...", "// TODO", "for brevity", and "the rest follows the same pattern" in both code and prose. - Deliverable Counting: Scopes the request, locks the number of expected deliverables, and cross-checks the output against that count before responding. - Clean Token-Limit Handling: When approaching token limits, stops at a clean breakpoint with a structured pause marker and resumes exactly where it left off on "continue". - Use Case: Ask for five complete React components or a full configuration file, and receive every item fully implemented with runnable code instead of skeletons or abbreviated examples. ## Quick Start Apply full-output enforcement 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 enforcement rules that ban placeholder patterns like "// rest of code" and require every requested deliverable to be fully written. Count the expected deliverables before generating and cross-check the output against that count.

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 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 phrases like "for brevity" or "the rest follows the same pattern". These indicate omitted content and produce non-runnable output.

When should full-output enforcement not be used?▼

Avoid it for exploratory brainstorming, quick drafts, or situations where a concise summary is explicitly requested. The enforcement optimizes for completeness, which adds length unsuited to high-level overviews.

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