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full-output-enforcement

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

Updated Aug 1, 2026
Search Tags:#code generation#llm prompting#output enforcement#anti-truncation#placeholder ban#complete output
One-click install
npx skills add https://github.com/dxiiren/project-skeleton --skill full-output-enforcement-dxiiren
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: full-output-enforcement
Source: https://github.com/dxiiren/project-skeleton/tree/main/.claude/skills-optional/taste-skill/output-skill
Command: npx skills add https://github.com/dxiiren/project-skeleton --skill full-output-enforcement-dxiiren

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? LLMs often truncate long outputs, insert placeholder comments like "// rest of code", or ask "want me to continue?" instead of delivering complete work. 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 "the rest follows the same pattern" in code and prose. - Scope Locking: Counts the requested deliverables before generating, then cross-checks the output against that count before responding. - Token-Limit Handling: When output approaches the token limit, it stops at a clean breakpoint and emits a [PAUSED — X of Y complete] marker, resuming exactly on "continue". - Use Case: Ask for a full implementation of five React components. Instead of receiving one complete component and four stubs, you receive all five fully implemented, or a clean pause marker with an exact resume point. ## Quick Start Apply the full-output-enforcement rules 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 "for brevity", require a deliverable count before generation, and mandate a cross-check of the output against the original request 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 like "[PAUSED — X of Y complete]". On "continue", resume exactly from that point with no recap or repetition.

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

Ban "// ...", "// TODO", "// implement here", "// similar to above", bare ellipses standing in for code, and prose like "the rest follows the same pattern" or "and so on" replacing actual content.

When should full-output enforcement not be used?▼

Avoid it for exploratory questions, quick prototypes, or when the user explicitly asks for a sketch or outline. Enforcing exhaustive output on small questions wastes tokens and slows iteration.

Does output enforcement work with any LLM or coding assistant?▼

Yes, it is a prompt-level instruction set with no code dependencies, so it works with any instruction-following LLM. It only changes generation behavior, not the model's underlying capabilities or context window size.

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