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ynd-compress
Workflow for compressing prompt and instruction files using LLM-powered techniques, with backup management and restore.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Workflow for compressing prompt and instruction files using LLM-powered techniques, with backup management and restore.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Development workflow for the ynh codebase. Build, test, lint, and format in the right order.
Maintain ynh vendor adapters against current vendor plugin specs. Use when updating adapters, checking spec compliance, or adding new vendor support.
Interactive wizard to create a ynh harness from scratch. Walks through naming, vendor selection, artifact scaffolding, and installation.
Guide graduation from a personal harness to a team setup with delegation. Creates a team harness that delegates to personal harnesses.
Guided walkthrough for using ynd inspect to bootstrap a project's AI skills and agents from its codebase signals.
Project scaffolding skill
| name | ynd-compress |
| description | Workflow for compressing prompt and instruction files using LLM-powered techniques, with backup management and restore. |
You are guiding a user through compressing their harness's prompt/instruction files to reduce token usage while preserving meaning.
Use after authoring or updating skills, agents, rules, or instructions. Compression reduces token count for files that will be loaded into every AI session. Particularly valuable for verbose instructions or detailed skills.
Help the user find files worth compressing. Good candidates are:
AGENTS.md filesFiles that should NOT be compressed:
Start with interactive mode so they can review the compression:
ynd compress skills/code-review/SKILL.md
This shows the original and compressed versions side by side with the reduction percentage. They can accept or skip.
Once they trust the quality, compress multiple files at once:
ynd compress -y skills/*/SKILL.md agents/*.md rules/*.md
Or compress everything discovered automatically:
ynd compress -y
Compression preserves YAML frontmatter structurally (it's never sent to the LLM), but always validate after:
ynd validate
ynd lint
Both should pass. If they don't, restore from backup and report the issue.
Every compression creates an automatic backup in ~/.ynd/backups/. Show the user how to manage them:
# See what backups exist for a file
ynd compress --list-backups skills/code-review/SKILL.md
# Restore the most recent backup
ynd compress --restore skills/code-review/SKILL.md
# Restore a specific older version
ynd compress --list-backups skills/code-review/SKILL.md # note the number
ynd compress --restore --pick 3 skills/code-review/SKILL.md
ynd compress -v claude to force a specific vendor if auto-detect picks the wrong one.