skill-pack/pos-skill-factory/SKILL.md
Create a new Claude Code skill from a description. 4 template patterns, quality validation, install to chosen location.
npx skillsauth add ai-mindset-org/pos-sprint pos-skill-factoryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Create a production-quality Claude Code skill from a natural language description. Uses 4 template patterns from real POS implementations, validates against a quality checklist, and installs to the right location.
Parse {idea} and determine:
When: skill examines a system, counts things, produces a score.
Structure: discover sources → scan each → aggregate → score → suggest gaps.
Real examples: /pos-audit (POS infrastructure), vault-cleanup (Obsidian maintenance), security-scan (secrets/permissions).
## Step 0: Discover sources
{read mcp.json, find files, check configs}
## Step 1-N: Scan each source
{extract data, categorize, count}
## Output: scored report
{box-drawing table with score breakdown}
## Scoring table
{component | points | criteria}
## Gap suggestions
{score range → recommended action}
When: skill pulls from multiple sources and synthesizes a result.
Structure: detect integrations → gather from each (with degradation) → synthesize → output in chosen format.
Real examples: /pos-morning (daily brief), /daily-focus (5 parallel agents → brief + visual card), /research (multi-angle Exa search → synthesis).
## Step 0: Detect integrations
{read mcp.json, build source map}
## Step 1: Gather from each source
{degradation chain: MCP → bash fallback → skip}
## Step 2: Synthesize
{derive insight from combined data}
## Step 3: Output
{multiple format options: terminal, file, message}
Key Pipeline pattern: always start with MCP detection and use graceful degradation chains:
Calendar: Krisp MCP → gcal script → skip
Tasks: Linear MCP → cache file → local TODO → skip
Messages: Telegram MCP → skip
When: skill takes input and produces a file or artifact.
Structure: parse input → apply template/rules → write output → verify.
Real examples: /pos-dashboard-gen (HTML dashboard), /deck (HTML presentations), /imagine (image generation via API).
## Step 1: Parse input
{args or interactive questions}
## Step 2: Build artifact
{HTML, markdown, image, etc.}
## Step 3: Write and verify
{write file, check size, open in browser/app}
## Design system (if visual)
{CSS variables, fonts, color scheme}
When: skill wraps an external service with opinionated defaults.
Structure: ToolSearch → build payload → show preview → confirm → execute → report.
Real examples: /linear-action (Linear CRUD with pre-fill), /telegram (MTProto messaging), /calendar (gcal with fallback chain).
## Step 0: Load MCP tools
{ToolSearch: "+server_name"}
## Step 1: Build payload
{pre-fill from context — session topic, recent work}
## Step 2: Preview → confirm
{show what will happen, ask y/edit/skip}
## Step 3: Execute and report
{MCP call, format result}
Key Integrator pattern: always pre-fill then confirm:
AIM-2054 · Sprint review prep · ◐ IP
action: update
comment: "completed slide deck, ready for review"
→ execute? [y/edit/skip]
Rules:
morning-brief, weekly-review, task-sortercheck-tasks, send-digest, scan-vaultdo-, run-, make- — be specificaim-)Validation: name must complete "I want to _____" naturally.
check-tasks"task-thing"Follow Claude Code skill spec exactly:
---
name: {skill-name}
description: {ONE line — what it does. Must fit in a skill listing.}
version: 1.0
user_invocable: true
arguments: # only if skill takes parameters
- name: {param}
description: "{what it controls}"
required: false
---
# {Title} — {Subtitle}
{2-3 sentences: what, why, when.}
## Step 0: {Detect/Discover} (if MCP-dependent)
{Read ~/.claude/mcp.json, ToolSearch for servers}
## Step N: {Action}
{Specific instructions with:
- Exact tool calls (Read, Write, Bash, Grep, Glob, ToolSearch)
- MCP function names
- Degradation chains (try A → try B → skip)
- What to do with the data}
## Output Format
{EXACT format with box-drawing characters:
┌─ ├─ └─ for trees
─── for dividers}
## Principles
- {Key behavior rule}
- {Graceful degradation}
- {What to never do}
## Common Mistakes
| Mistake | Fix |
|---------|-----|
| {wrong approach} | {correct approach} |
name, description (one line), version, user_invocable: true┌ ├ └ ─ │ for all structured output~ or $HOME, never hardcoded personal pathsShow the skill, then ask via AskUserQuestion:
Generated: /{skill-name}
Pattern: {A|B|C|D} — {name}
Lines: {count}
Sections: {list of ## headers}
Where to install?
1. Global (~/.claude/skills/) — available everywhere (Recommended)
2. Project (.claude/skills/) — only current directory
3. Show only — don't install yet
mkdir -p {path}/{skill-name}
Write SKILL.md with the Write tool (not bash).
Verify:
wc -l {path}/{skill-name}/SKILL.md
/{skill-name} installed
path: {full_path}/SKILL.md
size: {lines} lines
pattern: {A|B|C|D} — {name}
test: /{skill-name}
edit: {full_path}/SKILL.md
Validate all 7 before writing:
| # | Check | Criteria |
|---|-------|----------|
| 1 | Self-contained | Works without deps it can't detect |
| 2 | Graceful degradation | Missing source = skip, not error |
| 3 | Specific output | Exact format shown, not "generate report" |
| 4 | Monospace-first | Box-drawing chars for all structure |
| 5 | Tool-aware | Names which Claude Code tools to use |
| 6 | Right size | 40-150 lines. Longer → split into skills |
| 7 | Anonymized | ~ or $HOME, no personal paths |
Fix before preview if any check fails.
| User says | Skill | Pattern | Key feature |
|-----------|-------|---------|-------------|
| "summarize meetings and send to TG" | meeting-digest | B Pipeline | Krisp → synthesize → telegram send |
| "nag me about overdue tasks" | task-nag | D Integrator | Linear → filter overdue → urgent list |
| "weekly review from sessions" | weekly-review | B Pipeline | JSONL scan → topic extraction → report |
| "audit my security" | security-scan | A Audit | .env, secrets, permissions → scored |
| "HTML from markdown" | md-to-html | C Generator | Read .md → template → write .html |
| "check vault health" | vault-health | A Audit | File count, size, orphans → scored |
| Mistake | Fix | |---------|-----| | Description > 1 line | One sentence max — must fit skill listing | | Args skill doesn't need | Only add if behavior genuinely changes | | Vague output: "nice report" | Show EXACT format with box-drawing | | No MCP degradation chain | Always: MCP → file fallback → skip | | Skill > 150 lines | Split into 2 — a skill does ONE thing | | Missing Common Mistakes | Every skill needs 3-6 rows minimum | | Not checking mcp.json first | Step 0 discovers what's available |
testing
# YT Transcribe — YouTube → Whisper → Obsidian Транскрибирует YouTube-видео через mlx-whisper (Apple Silicon, Metal-native) с параллельными чанками. Fallback на openai-whisper если mlx недоступен. ## Какую боль закрывает - **Потерянный контент видео**: Посмотрел лекцию/подкаст — через неделю забыл 90%. Нет текстовой базы для поиска. - **Нет транскриптов для русского**: YouTube auto-captions для русского языка — мусор. Whisper даёт quality транскрипцию. - **Ручная обработка**: Переслушивать 2-
development
Интерактивный процесс написания текстов для вайб-маркетинга на основе Julian Shapiro framework. **Новые возможности (v2.0):** - Research & Gap Analysis (Perplexity → WebSearch fallback) - Scoring 0-5 вместо binary (Novelty + Resonance + Hook + Clarity) - AI-Slop Detection на всех этапах (10 типов patterns) - 3 варианта intro с self-scoring - Markdown export всех промежуточных результатов **Русские triggers:** "напиши пост по шапиро", "написать статью по фреймворку шапиро", "создай текст в стиле julian shapiro", "помоги написать контент по методу shapiro", "контент по julian shapiro фреймворку", "пост по julian shapiro", "напиши в стиле шапиро" **English triggers:** "write content using julian shapiro framework", "create post with shapiro method", "write article shapiro style", "help with julian shapiro writing" **Generic triggers:** "напиши статью", "помоги написать контент", "создай текст", "начать писать", "хочу написать пост", "нужна помощь с текстом", "write content", "write article", "создай контент", "придумай идею для статьи", or requests help with content creation process.
tools
# /tg-saved v2 — Telegram Saved Messages → Deep Analysis → Obsidian ## Назначение Скилл извлекает сообщения из Telegram "Избранное" (Saved Messages) за последние N дней, автоматически парсит контент всех ссылок в сообщениях (requests + BeautifulSoup, до 5000 символов на URL), затем для каждого сообщения запускает глубокий анализ через Claude CLI subprocess (модель Sonnet). Результат — подробная структурированная заметка в Obsidian `00-inbox/` с YAML frontmatter, секциями анализа, ссылками и ор
documentation
Делает LLM-выжимку из комментариев менеджеров об одном или нескольких подрядчиках. Используй этот скилл когда нужно понять что говорят менеджеры о конкретном подрядчике, или получить JSON с выжимкой для дальнейшей обработки.