What is content-generator?

A content-planning workflow that researches online interest and turns it into article ideas, summaries, publishing calendars, and promotion paths. It is aimed at technical publishing on platforms such as Dev.to, Medium, and Substack.

Use it to find keywords and trends, assess demand, generate article ideas, write abstracts, plan editorial calendars, and design subscriber funnels.

It reduces guesswork about which subjects to write about and how to adapt them for different publishing platforms. It also organizes research, topic validation, and planned follow-up content.

content-generator — Skill for Claude Code and Codex by noizu-labs-ml

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add noizu-labs-ml/NoizuPromptLingo --skill content-generator

Clone the repo

git clone --depth 1 https://github.com/noizu-labs-ml/NoizuPromptLingo

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/noizu-labs-ml/noizupromptlingo/content-generator/github.svg)](https://agentmods.dev/skills/noizu-labs-ml/noizupromptlingo/content-generator)

Your own site

<a href="https://agentmods.dev/skills/noizu-labs-ml/noizupromptlingo/content-generator"><img src="https://agentmods.dev/badge/skills/noizu-labs-ml/noizupromptlingo/content-generator/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/noizu-labs-ml/noizupromptlingo/content-generator"><img src="https://agentmods.dev/badge/skills/noizu-labs-ml/noizupromptlingo/content-generator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,597 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00046	$0.03597
Opus 5.5	$0.00018	$0.01439
Sonnet 5.5	$0.00009	$0.00719
Haiku 4.5	$0.00005	$0.00360

Measured 2mo ago against content hash 9bb32eb18a42, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

content-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

backend/priv/skills/content-generator/SKILL.md · 294 lines

How it starts

The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Generator

Research-driven content ideation, validation, and abstract creation pipeline for technical publishing.

Overview

This skill provides the operational pipeline for turning domain expertise into publishable content. It handles everything from initial trend research through validated, platform-optimized article abstracts ready for drafting.

Research trends across web, communities, social media, and video/podcast
Mine keywords with developer-query, long-tail, and problem-based strategies
Validate topic demand with scoring rubrics and competitive gap analysis
Generate article ideas in batch with full metadata and prioritization
Create platform-optimized abstracts (Substack, Medium, Dev.to)
Plan content calendars, series, and pillar strategies
Design conversion funnels from discovery to paid subscribers

Core Philosophy

Research before creation — Every article starts with evidence of demand, not intuition
Platform-native optimization — What works on Dev.to fails on Substack; optimize for the target
Evergreen bias with timely spikes — 70% searchable evergreen, 30% trending/timely
Competitive differentiation — If you can't beat existing content, don't write it
Pipeline discipline — Ideas flow through Research -> Validate -> Ideate -> Abstract -> Calendar

When to Use This Skill

Researching content opportunities — Trend analysis, community mining, gap identification
Doing keyword research — Developer queries, long-tail mining, problem-based keywords
Validating article demand — Demand scoring, competitive gap analysis, go/no-go decisions
Generating article ideas — Batch ideation, problem-solution mining, series planning
Creating abstracts/outlines — Full abstracts, quick batch abstracts, platform-optimized versions
Optimizing for platforms — Dev.to tags/timing, Substack conversion, Medium SEO
Planning content calendars — Monthly schedules, pillar mapping, cross-posting timelines
Designing content funnels — Discovery -> engagement -> conversion strategies

Read the full file on GitHub · 294 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 294 lines · 46 tokens per session scan A 9bb32eb18a42

Subscribe to this mod's changes

content-generator is a skill published in the GitHub repository noizu-labs-ml/NoizuPromptLingo (13 stars, last pushed 10d ago), licensed MIT. It adds 46 tokens to every session and 3,597 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-04.

Marketing and SEO Writing and docs

content-generator next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
content-generatornoizu-labs-ml/NoizuPromptLingo	Skill	13	10d ago	MIT	A	46	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code