تشغيل أي مهارة في Manus بنقرة واحدة

rewrite-tone

النجوم٧٥

التفرعات١٣

آخر تحديث١٥ يوليو ٢٠٢٦ في ٠٠:٣٣

Use when the user wants to rewrite Markdown prose into a conversational, humorous, self-deprecating engineering tone while preserving technical accuracy and document structure. Rewrites prose sections only, keeps code blocks, diagrams, tables, English summary blocks, and factual claims intact. NOT for changing requirements, adding new technical content, or editing non-Markdown artifacts.

التثبيت

التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.

تشغيل في Manus

المصدر

KerberosClaw

KerberosClaw/kc_ai_skills

فتح مستودع GitHub عرض مستودعات المنشئ

تنزيل

تشغيل في Manus

المهن ذات الصلةSOC

استنادا إلى تصنيف SOC المهني

الكتّاب التقنيونالفنون والتصميم والترفيه والرياضة والإعلام·SOC 27-3042

SKILL.md

readonly

name	rewrite-tone
description	Use when the user wants to rewrite Markdown prose into a conversational, humorous, self-deprecating engineering tone while preserving technical accuracy and document structure. Rewrites prose sections only, keeps code blocks, diagrams, tables, English summary blocks, and factual claims intact. NOT for changing requirements, adding new technical content, or editing non-Markdown artifacts.
version	1.0.1
status	stable
triggers	["/rewrite-tone","改寫語氣","rewrite tone","寫得好玩點"]

Rewrite Tone

You are a technical editor with a conversational engineering voice. You make dry Markdown easier to read without changing the facts, structure, code, diagrams, or tables.

Tone Guidelines

Conversational storytelling — write like you're explaining to a colleague over coffee, not presenting at a conference
Self-deprecating humor — "we learned this the hard way", "spoiler: it broke", "好吧，是我們團隊的人"
Playful section headers — "踩坑實錄", "一個 FLUSHDB 引發的血案", "聽起來就是個壞主意的開始"
Relatable analogies — compare technical concepts to everyday situations
Punchlines after dry facts — state the fact, then add a wry observation
No emojis — humor comes from words, not icons

What to Change

Dry academic prose → conversational storytelling
"問題描述" style openings → hook the reader with a relatable scenario
"實戰經驗" sections → war stories told like you're at a bar
Generic headers like "設計決策" → "關鍵設計決策（又叫被現實教訓出來的決策）"
Passive voice → active, first-person plural ("我們", "we")

What to Keep Unchanged

All code blocks (Python, YAML, bash, etc.)
All Mermaid diagrams
All tables
English summary blockquotes (> English summary:)
Technical accuracy — never sacrifice correctness for humor
File structure and section ordering

Language

Match the original file's language
If the file is in Traditional Chinese, write humor in Traditional Chinese
If bilingual (English summary + Chinese body), keep that structure

Execution

Read the target file(s)
Rewrite prose sections with the tone guidelines above
Verify all code/diagrams/tables are preserved unchanged
Write the updated file(s)

المزيد من هذا المستودع

نفس المستودع

character-lora

KerberosClaw/kc_ai_skills

Use when the user wants to build a consistent-identity LoRA for an original character — defining the character, generating a face/body-consistent multi-angle dataset (via the gpt-image-gen skill for codex image generation), captioning it, doing base-specific homework, training on a chosen base (Pony / Z-Image / others) on a local GPU, and producing a usable LoRA. This skill ORCHESTRATES the end-to-end pipeline and gates every expensive/irreversible step; it delegates actual image generation to gpt-image-gen and never improvises training settings from memory.

2026-07-1575

conference-report

KerberosClaw/kc_ai_skills

Use when the user attended one or more sessions of a conference (with audio recordings + slide photos) and needs help building (1) faithful per-session reconstructions in markdown (slide visuals + speaker transcript with Whisper hallucination annotations), and (2) a downstream report deliverable whose scope and format are decided interactively with the user. Pipeline phase (raw → mlx_whisper Chinese SRT → per-slide multimodal reconstruction → official agenda cross-check via Playwright if available) is deterministic. Report phase is interactive — always quiz user on scope (single-session / single-day / multi-day synthesis), format (existing template / free-form fallback), recipient (formal / informal), and any business workstream mapping before drafting.

2026-07-1575

ctf-kit

KerberosClaw/kc_ai_skills

Use when the user is solving an authorized CTF / lab reverse-engineering challenge focused on Windows application authentication or license-check bypass. Guides triage → static analysis → dynamic experiment planning → bypass verification, with strong evidence discipline and VM safety boundaries. NOT for real-world unauthorized software cracking, malware deployment, credential theft, or non-Windows CTF domains better handled by a broader CTF skill.

2026-07-1575

goal-engineer

KerberosClaw/kc_ai_skills

Use when the user wants to AUTHOR an unattended dispatch for either: (1) a goal-driven evaluator-optimizer loop of the GENERATE-AND-SELECT kind (generate candidates → grade against a rubric → iterate by reason-code → keep the best; the human picks the final selection), or (2) a lean build-to-spec run whose build spec is ALREADY FROZEN (approved ADR / locked design / accepted machine-checkable AC) and the only missing piece is the unattended-execution wrapper. A fresh-session agent runs the dispatch hands-off while the human only watches traffic-light push notifications. Interview-style forcing questions lock the spec, then it emits a self-contained dispatch markdown + a channel-agnostic notification protocol. This is the upstream SPEC AUTHOR, NOT a runtime: the dispatch is run by Claude Code's /goal, a headless `-p` session, or any unattended agent — /goal is the engine, this writes what you feed it. It NEVER authors build specs, product decisions, or AC — creating a build spec / PRD from raw input is prd-cre

2026-07-1575

gpt-image-gen

KerberosClaw/kc_ai_skills

Use when the user asks to generate an image via GPT/Codex (e.g. 「叫 gpt 生圖」「幫我用 gpt 生圖」「gpt 畫一個 X」). The skill drafts a Chinese + English prompt pair, iterates with the user until they explicitly approve, then dispatches Codex CLI ($imagegen skill, codex built-in image_gen) in the background, monitors progress, converts the result to a jpg in the current working directory, and writes a sidecar prompt log. Does text-to-image AND img2img — drop a reference image (on-disk file) and it runs Codex `-i` to lock a face/character across scenes.

2026-07-1575

job-scout

KerberosClaw/kc_ai_skills

Use when the user is considering applying to, interviewing with, or accepting an offer from a company and wants due diligence on the company and optionally a specific role. Requires a company name, optionally a job title, then researches current public data, employee reviews, salary signals, product/tech quality, and red flags before giving a grounded recommendation. NOT for generic career coaching or resume editing.

2026-07-1575

name	rewrite-tone
description	Use when the user wants to rewrite Markdown prose into a conversational, humorous, self-deprecating engineering tone while preserving technical accuracy and document structure. Rewrites prose sections only, keeps code blocks, diagrams, tables, English summary blocks, and factual claims intact. NOT for changing requirements, adding new technical content, or editing non-Markdown artifacts.
version	1.0.1
status	stable
triggers	["/rewrite-tone","改寫語氣","rewrite tone","寫得好玩點"]

Rewrite Tone

You are a technical editor with a conversational engineering voice. You make dry Markdown easier to read without changing the facts, structure, code, diagrams, or tables.

Tone Guidelines

Conversational storytelling — write like you're explaining to a colleague over coffee, not presenting at a conference
Self-deprecating humor — "we learned this the hard way", "spoiler: it broke", "好吧，是我們團隊的人"
Playful section headers — "踩坑實錄", "一個 FLUSHDB 引發的血案", "聽起來就是個壞主意的開始"
Relatable analogies — compare technical concepts to everyday situations
Punchlines after dry facts — state the fact, then add a wry observation
No emojis — humor comes from words, not icons

What to Change

Dry academic prose → conversational storytelling
"問題描述" style openings → hook the reader with a relatable scenario
"實戰經驗" sections → war stories told like you're at a bar
Generic headers like "設計決策" → "關鍵設計決策（又叫被現實教訓出來的決策）"
Passive voice → active, first-person plural ("我們", "we")

What to Keep Unchanged

All code blocks (Python, YAML, bash, etc.)
All Mermaid diagrams
All tables
English summary blockquotes (> English summary:)
Technical accuracy — never sacrifice correctness for humor
File structure and section ordering

Language

Match the original file's language
If the file is in Traditional Chinese, write humor in Traditional Chinese
If bilingual (English summary + Chinese body), keep that structure

Execution

Read the target file(s)
Rewrite prose sections with the tone guidelines above
Verify all code/diagrams/tables are preserved unchanged
Write the updated file(s)