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.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add Leonxlnx/taste-skill/full-output-enforcementCompatible with
Supported agents
| 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. |
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.
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.
When a response approaches the token limit:
[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.
Before finalizing any response, verify:
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfull-output-enforcementExecute the skills CLI command in your project's root directory to begin installation:
epx add Leonxlnx/taste-skill/full-output-enforcementFetches full-output-enforcement from Leonxlnx/taste-skill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/full-output-enforcement
Restart Cursor to activate full-output-enforcement. Access via /full-output-enforcementin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Registry listing for full-output-enforcement matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in full-output-enforcement — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: full-output-enforcement is focused, and the summary matches what you get after install.
I recommend full-output-enforcement for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
I recommend full-output-enforcement for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: full-output-enforcement is focused, and the summary matches what you get after install.
Registry listing for full-output-enforcement matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: full-output-enforcement is the kind of skill you can hand to a new teammate without a long onboarding doc.
full-output-enforcement is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in full-output-enforcement — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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