How to Handle Token Limit Splits with Output-Skill Enforcement Rules in taste-skill

The output-skill in the Leonxlnx/taste-skill repository eliminates truncation by enforcing a deterministic pause-and-resume protocol that stops generation at natural boundaries and continues from the exact next section without compressing or skipping content.

When a language model nears its token ceiling, standard truncation breaks multi-section outputs. The output-skill defined in skills/output-skill/SKILL.md treats every request as production-critical and prescribes a strict, agent-enforced workflow to handle token limit splits with output-skill enforcement rules. This guarantees that the final artifact is a lossless concatenation of complete, runnable pieces rather than a compressed summary.

What Is the Output-Skill?

The output-skill is a dedicated instruction set that tells the model never to truncate, summarize, or use placeholder shorthand. It is stored in skills/output-skill/SKILL.md and loaded at runtime through skill.sh, a registry script that maps a skill name to its SKILL.md file. The repository README.md documents that this skill should be added whenever the model keeps truncating output, and a related example appears in research/laziness/remediation/reference-prompts.md.

How Output-Skill Enforcement Rules Handle Token Limit Splits

The workflow is divided into five deterministic phases that transform a single long generation into a cleanly chunked, resumable session.

1. Scope-Locking

Before writing any code or prose, the model counts the distinct deliverables in the request—files, functions, or sections—and locks that scope. This creates a fixed checklist so the model knows exactly how many atomic pieces must be completed before the response is considered finished.

2. Full-Generation and Banned Patterns

During the Build phase, the model writes every deliverable in full. The skill explicitly bans compression patterns such as // ..., /* ... */, bare ellipsis, and deferral phrases like "let me know if you want me to continue." According to the Leonxlnx/taste-skill source code, these rules are enumerated in skills/output-skill/SKILL.md so the agent wrapper can scan for violations before returning output to the user.

3. Token-Limit Pause

When generated text approaches the token ceiling, the skill triggers a controlled pause at the next natural boundary. Lines 35-38 of skills/output-skill/SKILL.md explicitly require the following marker format:

[PAUSED — X of Y complete. Send "continue" to resume from: next section name]

X represents completed sections, Y is the total locked scope, and next section name is the exact heading or file that follows. Partial summarization or compression is never permitted.

4. Resuming

When the client sends continue, the agent reloads the same output-skill, re-reads the original request, and resumes generation precisely from the section named in the pause marker. No recap or duplicate content is inserted, ensuring the final output reads as one continuous, complete document.

5. Validation

Before any response is shipped, the agent runs a quick verification step defined at lines 44-49 of skills/output-skill/SKILL.md. This automated gate confirms:

• No banned patterns appear in the text.
• Every expected item from the locked scope is present.
• All code blocks are runnable and contain no placeholders.

If validation fails, the agent aborts and reports the deficiency instead of delivering a partial result.

Loading the Output-Skill at Runtime

The skill.sh registry resolves the skill name to its definition file. A typical shell session looks like this:

# Load the skill registry

source ./skill.sh

# Get the path to the output-skill definition

skill_path=$(./skill.sh output-skill)
echo "Using skill file: $skill_path"

Expected output:

Using skill file: skills/output-skill/SKILL.md

Handling a Pause in Practice

The following prompt template demonstrates how the pause marker appears in a live session:

You are an AI assistant. Apply the skill "full-output-enforcement" (see SKILL.md) to the following request:

Generate three JavaScript utility functions:
1. debounce(fn, wait)
2. throttle(fn, limit)
3. deepClone(obj)

[PAUSED — 2 of 3 complete. Send "continue" to resume from: deepClone implementation]

After receiving this marker, respond with continue. The agent then supplies the missing deepClone implementation, starting exactly where the pause indicated and without repeating the first two functions.

Automating Validation in Your Agent Wrapper

The following Python pseudo-code mirrors the validator an agent wrapper runs after each chunk and before emitting the final response:

def validate_output(text, expected_sections):
    banned = [
        r'//\s*\.\.\.', r'/\*\s*\.\.\.\s*\*/',
        r'\b\.\.\.\b',  # bare ellipsis

        r'let me know if you want me to continue',
    ]
    for pattern in banned:
        if re.search(pattern, text, flags=re.I):
            raise ValueError("Banned placeholder detected")

    missing = [sec for sec in expected_sections if sec not in text]
    if missing:
        raise ValueError(f"Missing sections: {missing}")

This wrapper guarantees that every chunk adheres to the zero-loss policy mandated by the output-skill.

Summary

• The output-skill lives in skills/output-skill/SKILL.md and is loaded via skill.sh.
• Scope-locking fixes the total deliverable count before generation starts.
• A pause marker in the form [PAUSED — X of Y complete. Send "continue" to resume from: next section name] creates deterministic, lossless boundaries.
• Resuming continues from the exact next section with no duplication.
• Agent-level validation at lines 44-49 of SKILL.md blocks banned placeholders and incomplete output.

Frequently Asked Questions

What is the exact pause marker format required by output-skill enforcement rules?

The required format is [PAUSED — X of Y complete. Send "continue" to resume from: next section name], where X is the number of finished sections, Y is the total scope, and next section name is the exact heading or file that follows. This syntax is explicitly mandated in skills/output-skill/SKILL.md at lines 35-38.

Which patterns does the output-skill ban during generation?

The skill forbids placeholder comments such as // ... and /* ... */, bare ellipsis (...), and deferral phrases like "let me know if you want me to continue." These patterns are listed in the skill definition so the agent wrapper can reject any output that attempts to truncate content disguised as code.

How does the agent resume after hitting a token limit?

When the user or client sends the cue continue, the agent reloads the output-skill, re-reads the original request, and begins generating from the exact section named in the pause marker. No recap is added, producing a seamless concatenation of complete chunks.

Where is the output-skill documented in the taste-skill repository?

The rule set is defined in skills/output-skill/SKILL.md. The registry script skill.sh maps the skill name to this path at runtime, while the repository README.md instructs users to apply the skill when the model consistently truncates output. An additional reference example appears in research/laziness/remediation/reference-prompts.md.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}