用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/notque/vexjoy-agent --skill condense命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Run the full evidence-to-live implementation workflow for large, multi-system, multi-wave, or CPU-delegated 5 Star Booker GM programs.
Classify user requests and route to the correct agent + skill. Primary entry point for all delegated work.
Structured multi-phase workflows: review, debug, refactor (tidy, clean up, untangle messy code without behaviour change), deploy, create, research.
基于 SOC 职业分类
正在显示 SKILL.md
| name | condense |
| description | Maximize information density: preserve all instructions, remove prose filler. |
| user-invocable | true |
| argument-hint | <file-or-glob> |
| allowed-tools | ["Read","Edit","Write","Bash","Grep","Glob"] |
| routing | {"triggers":["condense","reduce words","clarity pass","information density","remove prose","tighten","fewer words"],"pairs_with":["skill-creator"],"complexity":"Simple","category":"code-quality"} |
Strip prose filler from .md files. Preserve every instruction. This skill practices what it preaches.
Identify targets.
agents/*.md). Expand, list matches, confirm with user.Mechanical pre-pass (deterministic, run before LLM condensing): strip trailing whitespace and consecutive blank lines that inflate Opus token counts. The script handles the mechanical reduction so the LLM phase focuses on prose density.
python3 scripts/check-whitespace.py --fix <target-file-or-dir> # 0=clean, 1=violations fixed
Run on the scoped targets (defaults to agents/**/*.md and skills/**/*.md when no path given). Then proceed to the LLM pass on the same files.
Gate: At least one target file identified and readable; mechanical pre-pass run.
For each file:
KEEP (never cut):
CUT:
STYLE: Short sentences. Active voice. Concrete words. If you can cut a word without losing an instruction, cut it.
Before cutting any sentence: "If I remove this, does the reader lose an instruction, rule, or decision?" No = cut. Yes = keep.
Do not reorganize sections, change meaning, add ideas, alter paths/commands, drop tables or code blocks, or modify YAML frontmatter values.
For each condensed file:
python3 -c "import yaml; yaml.safe_load(open('<file>').read().split('---')[1])"
| File | Before | After | Reduction | table with word counts.Gate: YAML parses. No instructions lost. Reduction reported.
No prose to cut: Report 0% reduction, move to next file.
Instruction removed: Re-read original, restore missing instruction, re-verify.
YAML broken: Restore original frontmatter verbatim, re-condense body only.
Non-.md file: Skip with warning.