full-output-enforcement

Enforces complete code generation by banning placeholder patterns and truncation.

1|Updated Jan 10, 2024
One-click install
npx skills add https://github.com/noemdb/cfla --skill full-output-enforcement-noemdb
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: full-output-enforcement
Source: https://github.com/noemdb/cfla/tree/main/.agents/skills/full-output-enforcement
Command: npx skills add https://github.com/noemdb/cfla --skill full-output-enforcement-noemdb

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 incomplete and unusable code. This Skill overrides that default behavior so every requested deliverable is generated in full. ## Core Features & Use Cases - Placeholder Ban: Hard-fails on patterns like "// ...", "// TODO", "for brevity", and skeleton-only outputs, forcing real runnable code. - Deliverable Counting: Scopes the request, locks the expected number of deliverables, and cross-checks the output against that count before responding. - 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 multi-file component library or a complete configuration set, and receive every file finished, with no omitted sections or "continue the pattern" shortcuts. ## Quick Start Apply the full-output-enforcement skill and generate the complete implementation of all five requested components 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 instructions that ban placeholder patterns like "// rest of code" and require every requested deliverable to be generated in full. This Skill locks the deliverable count 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 without recap or repetition.

What placeholder patterns indicate incomplete AI-generated code?▼

Common signs include "// ...", "// TODO", "// implement here", "// similar to above", and prose like "for brevity" or "the rest follows the same pattern". These signal omitted logic rather than runnable code.

When should I not use full-output enforcement?▼

Avoid it for exploratory questions, quick prototypes, or when you only need a sketch of an approach. Forcing exhaustive output on small questions wastes tokens and slows iteration.

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 applies to any language or framework being generated.