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capel-fit

Normalize and fit CAPEL text to strict character limits using provided scripts.

Updated Feb 12, 2026
Search Tags:#character-limit#text-normalization#deterministic-scripts#admin-profile#qualification-answers#capel-fit
One-click install
npx skills add https://github.com/yutsukioka/un_job_application_helper --skill capel-fit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: capel-fit
Source: https://github.com/yutsukioka/un_job_application_helper/tree/main/.agents/skills/capel-fit
Command: npx skills add https://github.com/yutsukioka/un_job_application_helper --skill capel-fit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill provides deterministic character-counting and adjustment utilities to ensure CAPEL text fits within specified limits for Admin Profiles and qualification answers.

Core Features & Use Cases

  • Deterministic text fitting: uses scripts to measure and adjust text to target character bands.
  • Phrase replacements and filler-word trimming to reduce length without changing meaning.
  • Controlled expansion using placeholders when under target length.
  • Usage contexts: Admin Profiles and Qualification Answers where fixed-length entries are required.

Quick Start

Draft your paragraph, then run capel-fit with the desired character limits to validate and adjust it.

Frequently Asked Questions about capel-fit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I fit text to strict character limits for admin profiles?▼

To fit text to strict character limits for admin profiles, you can use deterministic scripts that measure text length and apply phrase replacements or filler-word trimming to adjust entries to the target length without changing meaning.

What is the best way to normalize text for fixed-length qualification answers?▼

Normalizing text for fixed-length qualification answers involves using deterministic scripts to measure character counts and trim filler words, ensuring your entries consistently fit within the required character bands.

How does deterministic text trimming handle overflow in per-entry CAPEL tasks?▼

Deterministic text trimming handles overflow by applying controlled phrase replacements and removing filler words to reduce length predictably, ensuring your text stays within specified character bands without altering the core meaning.

Can I expand text that is under the required character limit for templates?▼

Yes, you can expand text that is under the required character limit by using optional placeholder expansion, which controlledly increases the length to meet the target character band for consistent template entries.

Does capel-fit require any external dependencies to count characters and normalize text?▼

No, capel-fit does not require external dependencies to count characters and normalize text, as it operates using self-contained scripts like normalize_text.py, charcount.py, and fit_entry.py for deterministic text adjustment.

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