content-pipeline

content-pipeline is a skill for Claude Code, Codex from humanerd-drew/opencode-drewgent. It costs 0 tokens per session (12,469 once invoked), scanned A, original, MIT.

A monitoring setup that watches existing work or outside sources and turns selected topics into batches of content, such as a blog draft, an X thread, and a LinkedIn post.

In plain words
What is it for?
Use it to follow trends, create search-focused articles, document build work, and reuse one idea across several formats.
Why use it?
It helps keep content production organized over time without requiring a complex multi-step pipeline.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/humanerd-drew/opencode-drewgent/content-pipeline
Any agent
npx skills add humanerd-drew/opencode-drewgent --skill content-pipeline
Clone the repo
git clone --depth 1 https://github.com/humanerd-drew/opencode-drewgent

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.

agentmods badge for content-pipeline

README.md
[![agentmods](https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/content-pipeline.svg)](https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/content-pipeline)
Your own site
<a href="https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/content-pipeline"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/content-pipeline.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 12,469 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.12469
Opus 5 $0.00000 $0.06234
Sonnet 5 $0.00000 $0.02494
Haiku 4.5 $0.00000 $0.01247

Measured 4d ago against content hash d0ba0f73d85a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

content-pipeline 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 4d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/excalidraw-to-png.js, scripts/wordpress-mcp-server.js), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/content-pipeline/SKILL.md · 1,119 lines

How it starts

The opening of the file, as written. The whole thing — 1,119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content Pipeline Skill

Aggregator pattern: 이 skill은 content를 수집하지 않음. monitoring — watch, don't prompt.

  • Synthesize in batches. One cycle produces blog draft + X thread + LinkedIn.
  • Track narrative arc. Posts accumulate into a story. Season/episode structure keeps continuity.
  • Start simple. One agent profile + cron job + one tracking file. No multi-stage pipeline unless proven necessary.

Modes

Mode A: Aggregator (external → blog)

Collect from external sources (trend-harvester, SEO-harvester), select topics, assign to content-writer via kanban. Suitable for: trend posts, SEO-optimized evergreen, tool roundups.

Mode B: CMO Agent (internal work → content)

Single autonomous agent profile (content-manager) observes Drew's recent work and produces multi-format content. Runs daily at 12:00 KST via cron.

Trigger: Cron (0 12 * * *), deliver to Discord #content-channel. Profile: ~/.{{AGENT_NAME_LOWER}}/agents/content-manager.md (deepseek-v4-pro, tools: terminal, file, search, session_search, web) Skill prerequisites: content-pipeline (this skill), SVG knowledge, Excalidraw, Mermaid. Suitable for: build logs, troubleshooting deep-dives, architecture decisions, project retrospectives.

See references/cmo-agent-mode.md for the full implementation guide.

Mode B requires these knowledge base files (in P4-cortex/content/):

  • brand-guide.md — brand positioning, voice, audience
  • glossary.md — project terms ({{AGENT_NAME}}, M-LOG, PDC...)
  • content-inventory.md — published/drafted content for dedup
  • narrative_arc.md — episode tracking, season structure, continuity

The agent reads all four at the start of every cycle before gathering context.


Editorial North Star

YOUR_DOMAIN은 자동 뉴스 블로그가 아니라 Drew가 AI, 도구, 코드, 글쓰기, 시스템 설계를 통해 어떻게 사고하고 만드는지를 보여주는 개인 작업실이다.

공개 후보가 되는 글은 반드시 아래 등식을 만족해야 한다:

public-worthy content = 기록 + 해석 + 재사용 가능한 통찰

단순한 수집 결과, 출시 소식, 활동 보고, 링크 요약은 공개 draft로 만들지 않는다. 그런 항목은 raw 또는 archive에 남겨도 되지만 content board task로 승격하지 않는다.

Read the full file on GitHub · 1,119 lines

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.

  1. 4d ago First seen · 1,119 lines · 0 tokens per session scan A d0ba0f73d85a

Subscribe to this mod's changes

content-pipeline is a skill published in the GitHub repository humanerd-drew/opencode-drewgent (2 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 12,469 tokens. 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 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens