Skill Market

output skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

GitHub
githubcommunityagentaicodinglowcodenocodeskill
0.0
0 installs87.1K GitHub starsby Leonxlnx

Skill Introduction

Overview
Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

Core value

Turns reusable Documentation know-how into an installable skill, helping users complete github, community, agent, ai work faster.

Target users

  • Developers, testers, and maintainers who handle Documentation tasks in Focus Code.
  • Teams that already trust workflows or content from Leonxlnx.
  • Users who want standardized prompts, steps, or conventions instead of repeating setup work.

Best practices

  • Read the skill content first to confirm required inputs, expected outputs, and dependencies.
  • Try it on a small task before relying on it for critical work.
  • Add project-specific constraints such as coding style, target platform, test expectations, and delivery format.
  • For external sources, verify the source link, version, and recent maintenance activity.

Best use cases

  • Tasks related to github, community, agent, ai that need a reusable execution flow.
  • Converting a community repo, team convention, or personal workflow into day-to-day assistance.
  • Starting from a proven skill instead of writing prompts or procedures from scratch.

Limits and boundaries

  • Results depend on the quality of the original skill content and may need human correction.
  • It does not replace code review, tests, security review, or professional judgment.
  • External tools, APIs, account permissions, and local dependencies still need separate setup.

Differentiation

  • Structured around Documentation, making it easier to discover and reuse than loose prompt snippets.
  • Marked as GitHub, which helps users judge trust and maintenance expectations.
  • Keeps the original source link available for repository, documentation, or discussion follow-up.
  • Tagged with github, community, agent, ai, so it can be filtered by concrete task intent.

Install and use

Install
Copy Install Command
focus install output-skill-aec7f3
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SKILL.md

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name: full-output-enforcement description: Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

Full-Output Enforcement

Baseline

Treat every task as production-critical. A partial output is a broken output. Do not optimize for brevity — optimize for completeness. If the user asks for a full file, deliver the full file. If the user asks for 5 components, deliver 5 components. No exceptions.

Banned Output Patterns

The following patterns are hard failures. Never produce them:

In code blocks: // ..., // rest of code, // implement here, // TODO, /* ... */, // similar to above, // continue pattern, // add more as needed, bare ... standing in for omitted code

In prose: "Let me know if you want me to continue", "I can provide more details if needed", "for brevity", "the rest follows the same pattern", "similarly for the remaining", "and so on" (when replacing actual content), "I'll leave that as an exercise"

Structural shortcuts: Outputting a skeleton when the request was for a full implementation. Showing the first and last section while skipping the middle. Replacing repeated logic with one example and a description. Describing what code should do instead of writing it.

Execution Process

  1. Scope — Read the full request. Count how many distinct deliverables are expected (files, functions, sections, answers). Lock that number.
  2. Build — Generate every deliverable completely. No partial drafts, no "you can extend this later."
  3. Cross-check — Before output, re-read the original request. Compare your deliverable count against the scope count. If anything is missing, add it before responding.

Handling Long Outputs

When a response approaches the token limit:

  • Do not compress remaining sections to squeeze them in.
  • Do not skip ahead to a conclusion.
  • Write at full quality up to a clean breakpoint (end of a function, end of a file, end of a section).
  • End with:
[PAUSED — X of Y complete. Send "continue" to resume from: next section name]

On "continue", pick up exactly where you stopped. No recap, no repetition.

Quick Check

Before finalizing any response, verify:

  • No banned patterns from the list above appear anywhere in the output
  • Every item the user requested is present and finished
  • Code blocks contain actual runnable code, not descriptions of what code would do
  • Nothing was shortened to save space

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