Agent skill

Noise2blog

by Varnan-Tech in Varnan-Tech/opendirectory

Turns rough notes, bullet points, voice transcripts, or tweet dumps into a polished, publication-ready blog post.

MITAuto-check: notesWriting & Content

Install Noise2blog

skills CLI
$ npx skills add Varnan-Tech/opendirectory --skill noise2blog -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Varnan-Tech/opendirectory noise2blog --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/noise2blog .claude/skills/noise2blog && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
noise2blog
GitHub stars
674
Token cost
~2.4k tokens
SKILL.md length
914 words
Files
6 (incl. references)
Skills in repo
61
Repo updated
First seen
Licence
MIT

At a glance

Turns rough notes, bullet points, voice transcripts, or tweet dumps into a polished, publication-ready blog post.

  • Works in 7 steps: Setup Check → Read and Analyze Input → Choose Blog Post Style → …
  • Asked to write a blog post from notes
  • SKILL.md covers Step 1: Setup Check, Step 2: Read and Analyze Input, Step 3: Choose Blog Post Style and Step 4: Enrich with Tavily…, plus 3 more sections
  • Calls curl and python3; reaches api.tavily.com and generativelanguage.googleapis.com; needs GEMINI_API_KEY and TAVILY_API_KEY

What it does

Noise2blog is an agent skill from 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…

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `README.md`, `evals/evals.json` and `references/blog-format.md`). Compatibility notes: ["claude-code","gemini-cli","github-copilot"]

It sits in Writing & Content, covering Blog and article writing, Web search and Social media posts. It works with Tavily. The repository describes itself as: AI Agent Skills built for Founders who hate Marketing. The licence is MIT.

When your agent uses it

  • 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

Example prompts

  • “write a blog post from this”
  • “turn these notes into a post”
  • “expand this into an article”
  • “/noise2blog”

Requirements

  • Python 3
  • A credential in GEMINI_API_KEY
  • A credential in TAVILY_API_KEY
  • Compatibility (from SKILL.md): ["claude-code","gemini-cli","github-copilot"]

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Setup Check
  2. Read and Analyze Input
  3. Choose Blog Post Style
  4. Enrich with Tavily Research
  5. Generate the Blog Post
  6. Self-QA
  7. Output

What it can do on your machine

Read from SKILL.md and the folder at commit 62e437a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.tavily.com
    • generativelanguage.googleapis.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GEMINI_API_KEY
    • TAVILY_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    ["claude-code","gemini-cli","github-copilot"]

    From compatibility in the SKILL.md frontmatter.

Context cost

Noise2blog loads about 2.4k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 158 tokens; SKILL.md has 914 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~158
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:29
    google.com → Get API key. Add it to your .env file."

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Varnan-Tech/opendirectory at commit 62e437a, republished under its MIT licence (© Varnan-Tech). 914 words, ~2,386 tokens.

Download SKILL.mdSave it as .claude/skills/noise2blog/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
noise2blog
description
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".
compatibility
["claude-code","gemini-cli","github-copilot"]
author
OpenDirectory
version
1.0.0

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:

bash
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:

bash
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

Show full SKILL.md (293 more words)Show less

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:

bash
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:

bash
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:

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

dev.to:

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

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

Hashnode:

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

© Varnan-Tech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/noise2blog of Varnan-Tech/opendirectory.

  • SKILL.md
  • .env.example
  • README.md
  • evals/evals.json
  • references/blog-format.md
  • references/output-template.md

Open the folder on GitHubat commit 62e437a

Compare with similar skills

Noise2blog next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Noise2blog compared with similar skills
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Noise2blog this skillVarnan-Tech/opendirectory674—~2.4kAutomated safety check: NotesMIT
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Social Media Managementmanojbajaj95/claude-gtm-plugin1051 repos~3.9kAutomated safety check: PassMIT
Li RepurposeJakeschincariol/linkedin-agent-skill1.7k—~680Automated safety check: PassMIT
Content Repurposerguia-matthieu/clawfu-skills150—~1.4kAutomated safety check: PassMIT
RepurposeBlotato-Inc/blotato-skills183—~1.7kAutomated safety check: PassNone

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Works with

Questions about Noise2blog

What does Noise2blog do?

Turns rough notes, bullet points, voice transcripts, or tweet dumps into a polished, publication-ready blog post. Noise2blog is an agent skill from Varnan-Tech/opendirectory. Turns rough notes, bullet points, voice transcripts, or tweet dumps into a polished, publication-ready blog post.

When should I use Noise2blog?

Noise2blog fits situations like: 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.

How do I install Noise2blog in Claude Code?

Run `npx skills add Varnan-Tech/opendirectory --skill noise2blog -a claude-code`. Or copy the skill folder (skills/noise2blog in Varnan-Tech/opendirectory) into .claude/skills/noise2blog in your project. Claude Code loads it when a task matches its description.

How do I install Noise2blog in Codex?

Run `npx skills add Varnan-Tech/opendirectory --skill noise2blog -a codex`. Or copy the skill folder (skills/noise2blog in Varnan-Tech/opendirectory) into .agents/skills/noise2blog in your project. Codex loads it when a task matches its description.

Can I use Noise2blog in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Varnan-Tech/opendirectory --skill noise2blog -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/noise2blog, .gemini/skills/noise2blog, .github/skills/noise2blog and .opencode/skills/noise2blog in your project.

What does Noise2blog need to run?

Going by SKILL.md and its folder, Noise2blog needs the command-line tools its instructions call (curl and python3) and credentials named GEMINI_API_KEY and TAVILY_API_KEY. Our summary lists: Python 3; A credential in GEMINI_API_KEY; A credential in TAVILY_API_KEY. Compatibility (from SKILL.md): ["claude-code","gemini-cli","github-copilot"].

Does Noise2blog access the network?

SKILL.md names 2 domains. In commands or code: api.tavily.com and generativelanguage.googleapis.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Noise2blog safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Noise2blog use?

Noise2blog is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Noise2blog use?

About 2.4k tokens (SKILL.md is roughly 9.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.8k tokens, read only when the agent opens those files.

What are the alternatives to Noise2blog?

Skills that share tags, products or a category with Noise2blog: Content Repurposer (irinabuht12-oss/marketing-skills, 4.1k stars), Social Media Management (manojbajaj95/claude-gtm-plugin, 105 stars), Li Repurpose (Jakeschincariol/linkedin-agent-skill, 1.7k stars) and Content Repurposer (guia-matthieu/clawfu-skills, 150 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Noise2blog?

Varnan-Tech (a GitHub organization) maintains it in Varnan-Tech/opendirectory, which has 674 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on August 16, 2026.

Source: Varnan-Tech/opendirectory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.