full-output-enforcement

Enforces complete code generation by banning placeholder patterns and truncation.

1|Updated Aug 17, 2026
One-click install
npx skills add https://github.com/NalinDalal/skillset --skill full-output-enforcement-nalindalal
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: full-output-enforcement
Source: https://github.com/NalinDalal/skillset/tree/main/skills/quality/output-skill
Command: npx skills add https://github.com/NalinDalal/skillset --skill full-output-enforcement-nalindalal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? LLMs often truncate long outputs, insert placeholder comments like "// rest of code", or ask to continue later, leaving you with incomplete, non-runnable 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 implementations. - Scope Locking: Counts expected deliverables before generating and cross-checks the count before responding. - Token-Limit Handling: Pauses at clean breakpoints with a resumable marker instead of compressing or skipping content. - Use Case: Ask for a full multi-file component library; instead of receiving one complete file and four stubs, you receive all five files fully implemented, or a clean pause marker you can resume from. ## 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?▼

Use explicit output-enforcement instructions that ban placeholder patterns like "// rest of code" and require every requested deliverable to be generated fully. This Skill locks the deliverable count upfront and cross-checks it before responding.

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 and the next section. On "continue", resume exactly where you stopped without recap or repetition.

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

Ban patterns like "// ...", "// 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 code.

Does output enforcement work for non-code writing tasks?▼

Yes, the same rules apply to any exhaustive output request, including documentation, lists, and multi-section prose. The scope-counting and cross-check steps work for any countable set of deliverables.

When should I not use full-output enforcement?▼

Avoid it for exploratory brainstorming, quick prototypes, or when you explicitly want a short summary or skeleton. Enforcing completeness on open-ended tasks wastes tokens and slows iteration.