agentleFS
Sign inStart free
magicpro97magicpro97/vibeflow/.agents/skills/output-skill/SKILL.md

full-output-enforcement

Skill9 starsChanged 7 days agoMITView on GitHub

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.

We split this skill into the rules it gives an agent

8 rules. 8 are common, 0 are distinctive, and 0 are very specific to this project.

  • 8

    Common

    Most of the 10 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    Treat every task as production-critical.

    line 10
  2. Common:

    When a response approaches the token limit:

    line 30
  3. Common:

    Do not compress remaining sections to squeeze them in.

    line 32
  4. Common:

    Do not skip ahead to a conclusion.

    line 33
  5. Common:

    Write at full quality up to a clean breakpoint (end of a function, end of a file, end of a section).

    line 34
  6. Common:

    Before finalizing any response, verify:

    line 45
  7. Common:

    No banned patterns from the list above appear anywhere in the output

    line 46
  8. Common:

    Every item the user requested is present and finished

    line 47

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

Download now (ZIP)

Trending

Steady: 4 new projects took it in the last 4 weeks, 1× the 4 weeks before.thin data

Week of Aug 30: 0 new projectsWeek of Sep 6: 1 new projectWeek of Sep 13: 2 new projectsWeek of Sep 20: 1 new projectWeek of Sep 27: 0 new projectsWeek of Oct 4: 3 new projectsWeek of Oct 11: 1 new projectWeek of Oct 18: 0 new projects
Aug 2026Sep 2026Oct 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 8 in all, so this is a hint, not a trend.

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free