Community寫作與編輯github.com

Varnan-Tech/opendirectory

Turns rough notes, bullet points, voice transcripts, or tweet dumps into a polished, publication-ready blog post. Optionally enriches with Tavily research to add supporting data and credibility to claims. Use when asked to write a blog post from notes, turn rough ideas into an article, expand bullet points into a full post, clean up a voice transcript into a blog, or repurpose a tweet thread as an article. Trigger when a user says "write a blog post from this", "turn these notes into a post", "expand this into an article", "make this publishable", "I have rough notes write a blog", or "clean up this transcript".

opendirectory 是什麼?

opendirectory is a Claude Code agent skill that turns rough notes, bullet points, voice transcripts, or tweet dumps into a polished, publication-ready blog post. Optionally enriches with Tavily research to add supporting data and credibility to claims. Use when asked to write a blog post from notes, turn rough ideas into an article, expand bullet points into a full post, clean up a voice transcript into a blog, or repurpose a tweet thread as an article. Trigger when a user says "write a blog post from this", "turn these notes into a post", "expand this into an article", "make this publishable", "I have rough notes write a blog", or "clean up this transcript".

相容平台✓Claude Code~Codex CLI~Cursor✓Gemini CLI
npx skills add https://github.com/Varnan-Tech/opendirectory/tree/main/skills/noise2blog

Installed? Explore more 寫作與編輯 skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

Noise to Blog

Take any rough input (bullet points, voice transcripts, tweet dumps, or short drafts) and produce a polished, publication-ready blog post. Every claim traces to the source material or Tavily-verified research.


Critical rule: DO NOT INVENT SPECIFICS. Every claim, metric, and example in the blog post must come from the raw input or a Tavily search result. Never fabricate data, quotes, or outcomes.


Step 1: Setup Check

Confirm required env vars are set:

echo "GEMINI_API_KEY: ${GEMINI_API_KEY:+set}"
echo "TAVILY_API_KEY: ${TAVILY_API_KEY:-not set, Tavily enrichment will be skipped}"

If GEMINI_API_KEY is missing: Stop. Tell the user: "GEMINI_API_KEY is required. Get it at aistudio.google.com → Get API key. Add it to your .env file."

If TAVILY_API_KEY is missing: Continue. Note that Tavily enrichment will be skipped. The blog post will be based entirely on the provided content. This is fine for personal stories, tutorials from experience, or opinion pieces.

Confirm input is present. The user must provide one of:

  • Pasted text (bullet points, rough notes, transcript, tweet dump, short draft)
  • A URL to fetch

If no input, ask: "Share your rough notes, bullet points, or transcript. Paste them directly, or give me a URL to fetch the source."


Step 2: Read and Analyze Input

If input is a URL: Fetch the page content using WebFetch. Extract: title, author, publish date, all body text, key statistics, numbered lists, subheadings, quotes.

If input is pasted text: Read it directly. Identify the input type:

  • Bullet points or rough notes: fragmented ideas, incomplete sentences, stream of consciousness
  • Voice transcript: conversational, repetitive, filler words (um, uh, like, you know), meandering sentences
  • Tweet thread dump: short fragments, @mentions, hashtags, "1/8" numbering
  • Short draft: structured but thin, needs expansion and polish

QA checkpoint: State before continuing:

  1. Input type detected
  2. Core thesis or main argument in one sentence
  3. The 3-5 strongest insights, facts, or ideas from the raw content
  4. Any claims that need external verification (benchmarks, statistics, product comparisons, research findings)

If you cannot identify a core thesis, ask: "What's the single most important thing you want readers to take away from this?"


Step 3: Choose Blog Post Style

Four styles. Auto-detect from content signals. User override always respected.

StyleWhen to useSignals
Technical TutorialStep-by-step guide, how-to, code walkthroughNumbered steps, commands, code snippets, "how to" in content
Case StudyBefore/after story, build log, lessons learnedSpecific results, timelines, first-person journey
Thought LeadershipOpinion, argument, counterintuitive claim"I think", "the problem with X", contrarian position, debate framing
ExplainerWhat is X, why it matters, how it worksConcept-first, comparison-heavy, "most people don't know"

Detection logic:

  • Content has numbered steps or commands → Technical Tutorial
  • Content has before/after, specific metrics, or narrative arc → Case Study
  • Content argues against common wisdom or makes a strong opinion claim → Thought Leadership
  • Content explains a concept, tool, or trend for people unfamiliar with it → Explainer

State chosen style and reasoning. If ambiguous, pick one and note the choice.


Step 4: Enrich with Tavily Research

Skip this step silently if TAVILY_API_KEY is not set.

Search for supporting evidence for claims in the raw content that could benefit from verification or data. Good candidates:

  • Product benchmarks or performance numbers
  • Market statistics or industry trends
  • Technical comparisons ("X is faster than Y")
  • Any number the user mentioned from memory rather than a cited source

Run one Tavily search per claim that needs verification. Limit to 3 searches maximum to avoid over-sourcing:

curl -s -X POST "https://api.tavily.com/search" \
  -H "Content-Type: application/json" \
  -d '{
    "api_key": "'"$TAVILY_API_KEY"'",
    "query": "SPECIFIC_CLAIM_OR_TOPIC",
    "search_depth": "advanced",
    "max_results": 5,
    "include_answer": true
  }'

Keep results with score >= 0.65. Extract: title, url, content snippet.

Rules for using Tavily results:

  • Use them to support or verify claims already present in the raw input. Never introduce entirely new claims from search results.
  • Attribute sources naturally in the text: "according to [Source]", "data from [X] shows"
  • If no Tavily result confirms a claim, leave the claim unverified rather than substituting an unrelated result

Step 5: Generate the Blog Post

Read references/blog-format.md in full. Select the matching template from references/output-template.md. Internalize all rules before generating.

Write the Gemini request to a temp file to handle special characters safely:

cat > /tmp/noise2blog-request.json << 'ENDJSON'
{
  "system_instruction": {
    "parts": [{
      "text": "You are a tech writer who sounds like a real person. Rules: Active voice only. Short paragraphs, 1-3 lines max, then a blank line. Use contractions naturally (don't, won't, it's, can't, you're, they're). No em dashes — use a comma or period instead. No semicolons. Every sentence needs a concrete detail: a number, a tool name, a file name, a command, a result. No filler phrases: no 'In today's rapidly evolving', no 'Let's dive in', no 'It's worth noting', no 'In conclusion', no 'I hope this was helpful'. No banned words: incredible, amazing, leveraging, synergize, game-changing, groundbreaking, revolutionary, paradigm, cutting-edge, seamless, robust, unprecedented, delve, harness, utilize, transformative, disruptive, unlock, comprehensive, actionable, crucial, pivotal. Title must not start with I, My, or We. Open with a hook paragraph that does not announce the topic. Close with something actionable. Do not invent claims, metrics, or outcomes not present in the source material."
    }]
  },
  "contents": [{
    "parts": [{
      "text": "RAW_CONTENT_AND_INSTRUCTIONS_HERE"
    }]
  }],
  "generationConfig": {
    "temperature": 0.7,
    "maxOutputTokens": 4096
  }
}
ENDJSON

Replace RAW_CONTENT_AND_INSTRUCTIONS_HERE with:

  • The raw input content
  • The blog post style and structure instructions (from the selected template)
  • Any Tavily research results gathered in Step 4
  • Word target: 800-1,800 words

Post the request:

curl -s -X POST \
  "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d @/tmp/noise2blog-request.json \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['candidates'][0]['content']['parts'][0]['text'])"

Also produce:

  • (B) A 1-2 sentence meta description for SEO preview text
  • (C) One alternative title using a different hook angle

Step 6: Self-QA

Run every check and fix violations before presenting:

  • Title does not start with "I", "My", or "We"
  • Title is specific and conversational (not "A Comprehensive Guide to X" or "The Ultimate Guide to Y")
  • Opening paragraph hooks without announcing the topic ("In this post I will...")
  • No em dashes in any line
  • No semicolons
  • No paragraph longer than 3 lines before a blank line
  • No banned words: incredible, amazing, leveraging, game-changing, delve, harness, unlock, groundbreaking, cutting-edge, remarkable, paradigm, revolutionize, seamless, robust, utilize, unprecedented, comprehensive, actionable, crucial, pivotal
  • No invented data: every claim traces to the raw input or a Tavily result
  • Post does not end with "In conclusion", "To summarize", or "I hope this helped"
  • 800-1,800 words (state the word count)
  • Logical flow: opening → problem/context → body sections → actionable close

Fix any violation before presenting. State the final word count.


Step 7: Output

Present the full blog post in a code block.

Present the meta description and alternative title below the main post.

Ask: "Ready to copy this to your editor? If you're publishing to a specific platform, let me know and I can format the frontmatter."

On platform-specific request:

Ghost:

---
title: "POST_TITLE"
date: YYYY-MM-DD
tags: [tag1, tag2]
status: draft
---

dev.to:

---
title: POST_TITLE
description: META_DESCRIPTION
tags: [tag1, tag2, tag3]
published: false
---

Substack: Present as plain Markdown. Substack's editor imports markdown directly.

Hashnode:

---
title: POST_TITLE
subtitle: META_DESCRIPTION
tags: [tag1, tag2]
---

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Varnan-Tech/opendirectory

Use when the user asks to generate a blog cover image, thumbnail, or article header. Automatically uses modern typography, brand logos, and Google Search grounding to create beautiful 16:9 images with Gemini 3.1 Flash Image Preview.

Varnan-Tech/opendirectory

World-class brand strategist and naming expert. Uses an interrogation-led discovery phase to extract your brand's DNA, then applies scientific naming frameworks (Phonosemantics) and automated multi-TLD domain checking.

Varnan-Tech/opendirectory

Use when the user asks to generate or update a project's CLAUDE or AGENTS context file from a codebase scan. Writes a focused file under 100 lines containing only the non-obvious build commands, conventions, and gotchas Claude Code needs.

Varnan-Tech/opendirectory

Use when the user wants to verify cold emails, enrich a lead list, or autonomously guess email addresses from a CSV using ValidEmail.co or the open-source Reacher engine.

Varnan-Tech/opendirectory

Competitive intelligence orchestrator tracking companies across 8+ platforms (GitHub, Twitter, Reddit, HN, PH, YC Jobs) with heat scores and AI briefings.

Varnan-Tech/opendirectory

Give it your product URL or description. It finds your top 5 competitors, runs three-track PR research across all of them (editorial, podcasts, communities), identifies which channels appear most frequently, looks up the journalist or host for each, and returns a tiered outreach list with story angles and ready-to-send cold pitch drafts tailored to your product. Use when asked to find PR opportunities, discover where competitors got featured, build a media outreach list, find which journalists cover my space, or get pitch templates for press coverage.

Varnan-Tech/opendirectory

Generate high-converting, deep-dive growth case studies in MDX format. Use this skill when asked to write a case study or blog post about a company's growth, tech stack, or product-led strategy. It handles the full pipeline (researching the company via Tavily, generating a 16:9 cover image, quality checking the draft, uploading assets to cloud storage, and pushing directly to the target repository).

Varnan-Tech/opendirectory

Scans your project for outdated npm, pip, Cargo, Go, or Ruby packages. Runs a CVE security audit. Fetches changelogs, summarizes breaking changes with Gemini, and opens one PR per risk group (patch, minor, major). Includes Diagnosis Mode for install conflicts. Use when asked to update dependencies, check for outdated packages, open dependency PRs, scan for package updates, audit for CVEs, or flag breaking changes in upgrades. Trigger when a user says "check for outdated packages", "update my dependencies", "open PRs for dependency updates", "scan for CVEs", or "which packages need upgrading".

Varnan-Tech/opendirectory

Generates and updates README.md and API reference docs by reading your codebase's functions, routes, types, schemas, and architecture. Uses graphify to build a knowledge graph first, then writes accurate docs from it. Use when asked to write docs, generate a README, document an API, update stale docs, create an API reference from code, add an architecture section, or document a project in any language. Trigger when a user says their docs are missing, outdated, or wants to document their codebase without writing it manually.

Varnan-Tech/opendirectory

Evaluates expired domain candidates against a target niche, scores them by topical relevance, historical activity level, and history cleanliness, then outputs a ranked shortlist with explainable reasoning and risk flags.

Varnan-Tech/opendirectory

Brutally honest developer-experience audit for a GitHub repo. Scores 10 DX dimensions (time-to-first-success, README clarity, visual proof, install, quick-start, docs, examples, community, trust, marketing), writes a shareable roast in the requested tone (brutal/honest/kind), produces a prioritized action plan ranked by impact × effort, and sketches an ideal README. Trigger when user says "roast my repo", "audit my README", "dx audit", "developer experience review", "score my GitHub project", "before launch checklist", or "make my repo shareable".

Varnan-Tech/opendirectory

Drafts and designs a complete HTML email newsletter from a topic or content brief. Outputs paste-ready HTML for Loops, Mailchimp, Beehiiv, Resend, or any standard email platform. Includes subject line options and plain-text fallback. Trigger when a user says "write a newsletter", "draft an email newsletter", "create an HTML email", "design an email for my subscribers", or "write a newsletter about [topic]".

Varnan-Tech/opendirectory

Takes a GitHub PR URL or the current branch and writes a plain-English explanation of what it does and why, then posts it as a PR comment. Use when asked to explain a PR, summarize a pull request, write a plain-English description of a PR, add a summary comment to a PR, or understand what a PR changes. Trigger when a user says "explain this PR", "summarize this pull request", "what does this PR do", "add a comment explaining the PR", or shares a GitHub PR URL and asks what it does.

Varnan-Tech/opendirectory

Audit how often LLMs recommend your brand vs competitors and generate a GEO action plan.

Varnan-Tech/opendirectory

Takes a competitor's public GitHub repo URL, fetches their open issues via the GitHub REST API, filters noise locally, clusters issues into 6 demand categories, computes a demand score per issue and per cluster, and outputs a ranked demand gap report with a GTM messaging brief. Use when asked to scan a competitor's GitHub issues, find what their users are begging for, turn GitHub complaints into product positioning, identify competitor feature gaps, or generate messaging from real user demand. Trigger when a user says "scan competitor issues", "what are users asking for on X repo", "find demand gaps in Y", "turn GitHub issues into messaging", or "what should I build based on competitor complaints".

Varnan-Tech/opendirectory

Find recurring confusion in your repo's GitHub Discussions, rank it by urgency, and draft the actual docs fixes and content angles — with verbatim community quotes and source links as evidence.

Varnan-Tech/opendirectory

SEO keyword research workflow for blog generation using Google Trends data. Use when writing blog posts, planning content calendars, or optimizing articles for search engines. Finds breakout keywords, builds content structure, and generates SEO-optimized blog outlines targeting tech and developer audiences.

Varnan-Tech/opendirectory

Generates a professionally designed case study PDF for B2B SaaS sales and marketing. Supports 7 page layouts, 9 style presets, 1-4 page output. Trigger when user says "create a case study", "write a customer story", "make a case study PDF", "design a success story", "turn this customer win into a PDF".

Varnan-Tech/opendirectory

Generates data visualization charts (bar, line, area, pie, doughnut, scatter, radar, treemap) as PNG using Apache ECharts v6. 1080×1080px default, 5 style presets, highlight annotations. Trigger when user says "create a chart", "visualize data", "make a bar chart", "line graph", "pie chart", "data visualization", "chart this data", "plot", "graph", or "visualize these numbers".

Varnan-Tech/opendirectory

Fetches low-star App Store and Google Play reviews, clusters them into broken-promise patterns, and generates a ranked copy brief with positioning opportunities.

相關技能