販売代理店

4つのエージェントが毎日稼働している。1つはトレンドトピックからブログ記事を作成する。1つはPostHogを分析し、ランディングページで修正すべき点を指摘する。1つは各記事をInstagramのカルーセル形式に変換する。1つはRedditで助けを求めているスレッドを見つけ、返信の下書きを作成する。

一度設定すれば、それらはcronスケジュールに従って稼働する。機能開発に専念している間も、トラフィックは増加し続ける。

エージェントの定義が必要か？ 完全な定義 にスキップし、プロジェクトにコピー＆ペーストすればよい。

このシステムが果たす役割

SaaSの創業者の多くは、プロモーションを週末の雑用として扱っている。思い出した時にブログ記事を書く。時間がある時にSNSでシェアする。翌月にアナリティクスを確認する。そのやり方では、訪問者はせいぜい数百人程度が限界だ。

このシステムは、プロモーションをコードとして扱う。4つのエージェント、4つのチャネル、1つのスケジュール。各エージェントは前のエージェントの出力を読み込むため、パイプラインは自己駆動する。

フローは以下の通りだ：

blog-writer  →  posthog-analyst  →  carousel-maker  →  reddit-scout
   (SEO)          (optimize)         (Instagram)        (Reddit)

Blog Writerが記事を公開する。PostHog Analystが訪問者の反応を監視する。Carousel Makerが記事をスライドに変換する。Reddit Scoutが、そのトピックがすでに議論されているスレッドを見つけ、役立つ返信を起草する。

スケジュールの仕組み

Claude Codeにはスケジュールタスク機能が組み込まれている。設定方法は2通りある：

デスクトップアプリ：サイドバーの**「Schedule」をクリックし、「+ New task」**を押す。名前を付け、エージェントのプロンプトを貼り付け、頻度を選択する。各タスクは、ファイル、MCPサーバー、スキルへのフルアクセス権を持つ新しいセッションを起動する。

CLI：ターミナルから /schedule を実行し、スケジュールされたエージェントの作成、一覧表示、管理を行う。タスクは ~/.claude/scheduled-tasks/<task-name>/SKILL.md に YAML のフロントマター付きで保存される。ファイルを直接編集すると、次回の実行時に変更が反映される。

4つのタスク、4つの実行頻度：

各タスクは、開いているウィンドウには影響しない新しいセッションを起動する。完了すると通知が表示され、Claudeの処理内容を確認できる。Channelsに接続すれば、出力はTelegramやDiscordに届く。

エージェント1：ブログライター

ブログライターは、トレンドトピック（Hacker News、GitHub Trending、Xからのもの）のデイリーダイジェストを読み込み、SEOに最適化されたブログ記事を作成する。すべての記事はロングテールキーワードをターゲットにしている。すべての記事は厳格な構成に従う：問題、クイックウィン、詳細セクション、まとめ。

これが「ChatGPTを使ってブログ記事を書く」と何が違うのか：このエージェントは既存のブログを読み込み、あなたの文体を理解し、コンテンツの柱を確認した上で、すでに公開されている記事に合ったスタイルで執筆する。また、フロントマター、サイロルーティング、メタタグの処理も行う。

1日1記事。それぞれがGoogleにインデックスされる新しいページとなる。GEO最適化と組み合わせれば、AIアシスタントが単に順位をつけるだけでなく、あなたの記事を引用するようになる。30日後には、30のキーワードターゲットページが24時間体制で働き始める。

エージェント2：PostHog Analyst

訪問者がすぐに離脱してしまうなら、トラフィックは意味をなさない。PostHog AnalystはMCPサーバー経由でPostHogインスタンスに接続し、スクロール深度、CTAクリック率、直帰率、ページ滞在時間といった実際のデータを取得する。

単に数字を並べるだけではない。データを解析し、前週と比較して、具体的な推奨事項を作成する。「『CTA』を画面上部（above the fold）に移動させよ。先週のクリック率は2.1%だった。スクロールせずに『CTA』が見えるページの平均クリック率は5.8%だ。」

その提案を読み、変更を加える（あるいはクロードに実行させる）。翌日、エージェントは数値に変化があったかを確認する。

エージェント3：カルーセル・メーカー

すべてのブログ記事は、同時にInstagramのカルーセルでもある。カルーセル・メーカーは記事を読み込み、核心となる教えを抽出し、7枚のスライドからなるTSXカルーセルを作成する。背景はダーク、アクセントカラーはコーラル、スライド1にはフック、スライド2から6には価値、スライド7にはCTAを配置する。

このエージェントはPlaywrightを使用して、スライドを1080x1350ピクセルのPNGファイルとして出力する。FigmaもCanvaも不要。手作業でのデザイン作業も一切ない。

週に3つのカルーセル。それぞれがフォロワーをブログ記事へと誘導する。

エージェント4：Reddit Scout

Redditは、クリエイターが本音で質問を投げかける場だ。Reddit ScoutはPythonスクリプトを実行し、8つのサブレディットからトピック領域に合致するスレッドをスクレイピングする。各スレッドを、投稿日時、アップボートの増加率、コメント数で評価する。

上位のスレッドに対して、エージェントが返信の下書きを作成する。売り込みではない。ブログ記事で既に扱っている内容に基づき、その人の質問に対する真摯な回答だ。返信には製品名は一切含まれない。ただ役立つ情報を提供するだけだ。

あなたは下書きを確認し、必要に応じて編集し、自分で投稿する。本物のエンゲージメントであり、スパムは一切ない。

30日後の結果

計算は単純だ。1日1本のブログ記事を投稿し、それぞれ月間検索数500～2,000のキーワードをターゲットにする。Googleは48時間以内にそれらをインデックス化する（IndexNowを使えばさらに速い）。30日後：

• インデックスされたページ数：30ページ
• 各ページが月間50～300人のオーガニック訪問者を集める
• Instagramからのカルーセルが、さらに10～20％のトラフィックを誘導
• Redditの返信がスレッドから温かいリファラルトラフィックを誘導

これらを合わせると、相乗効果を生むチャネルから月間10,000人以上の訪問者が得られる。新しい投稿が加わるたびに総数は増える。すべてのカルーセルは投稿へと誘導する。すべてのRedditへの返信は関連コンテンツへリンクする。

エージェントの定義

以下の4つのファイルをプロジェクト内の.claude/commands/にコピーする。CLIの/schedule、またはデスクトップサイドバーから、それぞれをスケジュールされたタスクとして設定する。各エージェントは、実行のたびにコードベース、MCPサーバー、およびスキルへのフルアクセス権を得る。

エージェント1：ブログライター (.claude/commands/blog-writer.md)

---
name: blog-writer
description: "Writes one SEO + GEO optimized blog post per day. Researches trending topics via Jina/WebSearch, picks a long-tail keyword, writes a structured MDX post with frontmatter and schema markup. Reads existing posts to match voice and avoid duplicate keywords."
tools: Read, Write, Edit, Bash, Glob, Grep, WebSearch, WebFetch
mcpServers:
- jina
- context7

skills:
- nextjs-seo
- ai-seo

maxTurns: 60
permissionMode: bypassPermissions
---

# /blog-writer

Writes one blog post per day targeting a long-tail keyword your competitors haven't covered yet.

## Skills to Load

- `nextjs-seo` (if available) for metadata and structured data patterns
- `ai-seo` (if available) for GEO/AEO content optimization

## MCP Servers Used

- `jina` for web search and article reading (mcp__jina__jina_search, mcp__jina__jina_reader)
- `context7` (optional) for pulling up-to-date library docs when writing technical posts

## Pre-flight

1. Read `docs/project/product-overview.md` to understand the product, audience, and positioning.
2. Read `docs/project/brand-guidelines.md` for voice, tone, and vocabulary rules.
3. Scan existing posts to avoid duplicate keywords:

   ```bash
   grep -r "^title:" content/blog/ --include="*.mdx" | sort

1. Read the last 3 published posts to match voice and sentence cadence.

Phase 1: Topic Research

Use Jina search to find what's trending in your niche today:

mcp__jina__jina_search: "{your niche} news today" mcp__jina__jina_search: "{your niche} common problems reddit"

Pick a topic that: - Has a long-tail keyword (3-5 words, 500-2,000 monthly searches)

• No existing post covers it (check the grep output from pre-flight)
• Maps to a real problem your product solves, even indirectly
• Works as a "how to" or "what is" query (these index fastest)

Phase 2: Research the Topic

Read 3-5 top sources on the topic using Jina reader:

mcp__jina__jina_reader: "https://example.com/article-about-topic"

Extract concrete facts, numbers, code patterns, and common mistakes. Never invent data points.

Phase 3: Write the Post

Output path: content/blog/{category}/{slug}.mdx

Frontmatter:

yaml --- title: "Keyword-Front-Loaded Title" description: "One sentence. ~120 chars. Zero 4-word overlap with opening paragraph." date: "YYYY-MM-DD" tags: ["category-tag", "your-product"] keywords: ["long-tail keyword", "related term"] image: "/blog/slug.png" readingTime: "N min read" published: true ---

Post skeleton:

• Opening: 2-4 punchy sentences. State what the reader gets. Lead with outcome.
• Problem section: 2-3 sentences. Concrete pain the reader has felt.
• Quick Win: One code block or config snippet that works immediately.
• 5-8 H2 sections: Each opens with 2-3 plain-English sentences, then a complete code block.
• Takeaway: 2-3 sentences. Reframes the opener. Never "in conclusion."

Phase 4: GEO Optimization

Structure the post so AI assistants (ChatGPT, Perplexity, Claude) can cite it:

• Open sections with clear one-sentence definitions ("X is Y that does Z.")
• Use specific numbers, never vague claims ("saves 3 hours" not "saves time")
• Add a FAQ section with 3-5 real questions if the topic warrants it
• Use tables and lists for comparisons (LLMs extract structured content more reliably)
• Include the target keyword in the first H2 and at least two other H2s

Phase 5: Verify

bash cd webapp && npx tsc --noEmit

Must pass clean. Check that description and first paragraph share zero 4-word phrases.

Writing Rules

• Short paragraphs: 1-3 sentences. 65% should be 1-2 sentences.
• Zero em-dashes. Use periods, commas, or colons.
• Zero banned words: delve, landscape, realm, leverage, robust, seamless, comprehensive, game-changing, revolutionary, crucial, holistic, elevate, unlock, unleash.
• Lead with outcome, not process. "You" in 50% of paragraphs. Zero "I".
• Colon before every code block. Every code block complete and self-contained.
• Every sentence readable by a non-developer.

Error Recovery

• tsc fails: fix type errors in frontmatter or MDX syntax, re-run.
• Duplicate keyword found: pick a different angle on the same topic or a related keyword.
• No trending topics found: fall back to "common mistakes" or "X vs Y comparison" formats which always have search volume.

**Agent 2: PostHog Analyst** (
`.claude/commands/posthog-analyst.md`)

```markdown
--- name: posthog-analyst description: "Connects to PostHog via MCP, auto-discovers tracked events, pulls landing page metrics for the last 7 days, compares week-over-week, and writes one specific fix recommendation backed by data. Optionally applies the fix directly." tools: Read, Write, Edit, Bash, Glob, Grep mcpServers: - posthog

skills: - posthog-analytics

maxTurns: 40 permissionMode: bypassPermissions ---

<h1>/posthog-analyst</h1>

Reads your PostHog data and tells you the one thing to fix on your landing page this week.

<h2>MCP Servers Used</h2>

- 

`posthog` (required) for all analytics queries (mcp__posthog__query-run, mcp__posthog__insights-get-all, mcp__posthog__insight-query, mcp__posthog__projects-get)
<h2>Pre-flight</h2>

1. Verify PostHog MCP is connected:

Call mcp__posthog__projects-get

If it fails: stop and report "PostHog MCP not connected. Run `npx @posthog/wizard mcp add` and restart Claude Code."

1. Read

`docs/project/product-overview.md` for product context (what matters to track).Read `docs/built/analytics.md` (if it exists) for the event taxonomy and funnel definitions.
<h2>Phase 1: Discover Events</h2>

If no event map exists yet, auto-discover what's being tracked:

``` call mcp__posthog__event-definitions-list to see all custom events. Call mcp__posthog__properties-list to see available properties. ```

Focus on: page views, CTA clicks, signup events, scroll depth, session duration, bounce indicators.

<h2>Phase 2: Pull This Week's Data</h2>

Use PostHog MCP query tools to pull the last 7 days:

```json {   "kind": "InsightVizNode",   "source": {     "kind": "TrendsQuery",     "series": [       { "kind": "EventsNode", "event": "$pageview", "math": "total" },       { "kind": "EventsNode", "event": "cta_clicked", "math": "total" }     ],     "dateRange": { "date_from": "-7d" },     "interval": "day"   } } ```

Pull these metrics: 1. Page views by URL (breakdown by $current_url)
2. CTA click rate (cta_clicked / $pageview on the landing page)
3. Scroll depth distribution (if scroll_depth_reached events exist)
4. Bounce rate (single-page sessions / total sessions via HogQL)
5. Session duration (median and p75 via HogQL:

`median(session_duration)`)Signup funnel conversion (if signup events exist) Then pull the SAME queries for the previous 7 days (date_from: -14d, date_to: -7d) for comparison.

<h2>Phase 3: Analyze and Compare</h2>

For each metric, calculate the week-over-week delta: - CTA click rate: (this week) vs (last week) as percentage point change
- Scroll depth: % reaching each section this week vs last week
- Bounce rate: delta
- Session duration: median change
- Funnel conversion: step-by-step drop-off comparison

Rank regressions by impact. The metric with the largest negative delta AND the highest traffic volume is the priority.

<h2>Phase 4: Write Recommendation</h2>

Find the single biggest regression or opportunity. Write one specific paragraph:

1. Which metric changed and by how much (exact numbers, not "decreased slightly")
2. Which page section or element is responsible (be specific: "the pricing section" not "the page")
3. What to change (concrete: "Move the primary CTA above the pricing table. Add a second CTA after the feature grid." not "improve the CTA placement")
4. Expected impact based on the data delta

<h2>Phase 5: Optionally Apply the Fix</h2>

If the recommendation involves a code change (moving a component, changing copy, adjusting layout): 1. Find the relevant file in

`app/(marketing)/page.tsx` or the component it importsMake the changeRun `npx tsc --noEmit` to verifyReport what was changed If the fix requires design review or A/B testing, skip this phase and just report the recommendation.

<h2>Output</h2>

Write to 
`docs/analytics/weekly-{YYYY-MM-DD}.md`:

```markdown <h2>PostHog Weekly: {date}</h2>

<h3>Key Metrics (vs previous week)</h3> | Metric | This Week | Last Week | Delta |
| --- | --- | --- | --- |
| Page views | {n} | {n} | {+/-n%} |
| CTA click rate | {n%} | {n%} | {+/-pp} |
| Bounce rate | {n%} | {n%} | {+/-pp} |
| Median session | {n}s | {n}s | {+/-n%} |
| Signup conversion | {n%} | {n%} | {+/-pp} |

<h3>Top Regression</h3> {one paragraph}

<h3>Recommendation</h3> {one paragraph with the specific change}

<h3>Applied</h3> {YES with file path, or NO with reason} 

Rules

• Never guess. Only recommend changes backed by a measurable delta.
• One recommendation per run. The most impactful one.
• If all metrics are stable or improving, say "all metrics stable" and stop.
• A 44% scroll depth is only bad if it dropped from a higher number. Context matters.
• Never track PII beyond email/name. Never log passwords, tokens, or credit card data.

Error Recovery

• PostHog MCP call fails: check project ID, try

mcp__posthog__switch-project if multiple projects exist.No events found: report "No custom events tracked yet. Run /analytics first to set up event tracking."Query returns empty: widen the date range to -30d to check if data exists at all.```

Agent 3: Carousel Maker ( .claude/commands/carousel-maker.md)

--- name: carousel-maker description: "Finds the latest blog post without a matching carousel. Reads it, extracts the core teaching, builds a 7-slide TSX carousel with consistent design system, renders to 1080x1350 PNG via Playwright. Self-verifies every slide before reporting done." tools: Read, Write, Edit, Bash(npx tsx *), Bash(./scripts/*), Glob, Grep skills: - carousel-design
- brand-voice

maxTurns: 80 permissionMode: bypassPermissions ---

<h1>/carousel-maker</h1>

Turns blog posts into Instagram carousels. One post in, seven slides out.

<h2>Pre-flight</h2>

1. Find the latest blog post without a carousel:

   ```bash
   # List all blog posts
   ls -t content/blog/**/*.mdx | head -10
   # List existing carousels
   ls output/carousels/

Match by slug. Pick the most recent unmatched post.

1. Read the blog post fully. Extract:

• The core problem it solves
• The key insight or "aha" moment
• 3-4 concrete teaching points (one per value slide)
• The best CTA angle (what should the reader do after?)

1. Read the last 2 shipped carousels under

output/carousels/ for design patterns and component usage. Study, don't copy.

1. Read

src/components/index.ts to see what's available to import.

Carousel Structure

7 slides. Each 1080x1350 (4:5 aspect ratio for Instagram feed).

• Slide 1 (Hook): One headline that stops the scroll. Max 8 words in the big line. Must include a bespoke visual (chart, icon grid, mockup). Never a plain text slide.
• Slides 2-6 (Value): Each teaches one point. Max 25 words per slide. Each slide uses a visual element to support the text.
• Slide 7 (CTA): Comment keyword in large gradient text. "Follow @YOUR_HANDLE for more." Logo + domain.

Design System

Define your brand tokens at the top of the file. Consistency matters more than novelty:

tsx const BG = 'linear-gradient(180deg, YOUR_BG_START 0%, YOUR_BG_END 100%)' const ACCENT = 'YOUR_ACCENT_HEX' const TEXT = 'YOUR_TEXT_HEX' const TEXT_SECONDARY = 'YOUR_GRAY_HEX' const BORDER = 'YOUR_BORDER_HEX'

Layout Rules

• Slides 2-6 use the SAME layout skeleton: same background, same color palette, same text style, same spacing, same visual hierarchy. Consistency across all value slides.
• Only the hook (slide 1) and CTA (slide 7) break the pattern.
• All custom visuals are inline components in the same TSX file. Never modify shared component files.
• Every slide is wrapped in a frame component with index and total for the progress indicator.

Content Rules

• No jargon. Write for someone who has never coded. If a technical term is needed, explain it in the same sentence.
• Max 25 words per slide body (excluding code snippets).
• No price on slides. Price goes in the Instagram caption.
• No glow effects, drop shadows, or radial halos.
• No colored left-border accents on cards.
• Content must not overlap the footer/brand bar area.

Render and Verify

bash npx tsx scripts/render-tsx.ts output/carousels/{YYYY-MM-DD}-{slug}/carousel.tsx

After rendering, open EVERY PNG and check: 1. Text is readable at phone screen size 2. No content overlaps the footer 3. No dead space (80px+ empty areas) 4. Hook slide headline reads in under 3 seconds 5. A non-technical person would understand each slide

If any check fails, fix and re-render.

Output

output/carousels/{YYYY-MM-DD}-{slug}/carousel.tsx output/carousels/{YYYY-MM-DD}-{slug}/slide-01.png through slide-07.png

Error Recovery

• Render fails: check TSX syntax, verify all imports exist in

src/components/index.ts.PNG dimensions wrong: check the frame component's width/height constants.Text overflows: reduce word count or font size. Never let text clip.```

Agent 4: Reddit Scout ( .claude/commands/reddit-scout.md)

--- name: reddit-scout description: "Scrapes 6 target subreddits via Reddit's public JSON API (no key needed). Scores threads by recency, relevance, and opportunity. Drafts value-first replies based on published blog content. Zero self-promotion. User reviews and posts manually." tools: Read, Write, Bash(curl *), Bash(python3 *), Glob, Grep mcpServers: - jina

skills: - reddit-culture
- brand-voice

maxTurns: 50 permissionMode: bypassPermissions ---

<h1>/reddit-scout</h1>

Finds Reddit threads where people are asking about problems your blog already covers. Drafts replies. You review and post.

<h2>MCP Servers Used</h2>

- 

`jina` (optional) for reading linked articles in threads via mcp__jina__jina_reader
<h2>Pre-flight</h2>

1. Read your blog post index to know what topics you can actually help with:

   ```bash
   grep -r "^title:\|^description:" content/blog/ --include="*.mdx" | head -30

1. Read

docs/project/product-overview.md to understand the product (so you can avoid accidentally shilling it).

Phase 1: Scrape

Hit Reddit's public JSON endpoints. No API key needed:

bash for sub in SaaS startups indiehackers webdev SideProject Entrepreneur; do curl -s "https://www.reddit.com/r/$sub/hot.json?limit=30" \ -H "User-Agent: scout/1.0" > "/tmp/reddit-$sub.json" done

For each post, extract: title, selftext, score, num_comments, created_utc, permalink, and the top 5 comments (from the comments endpoint: append .json to the permalink).

Phase 2: Score

Rate each thread on three axes (5 points each, max 15):

Recency - Last 6 hours: 5

• Last 24 hours: 4
• Last 48 hours: 3
• Last 7 days: 1
• Older: 0

Relevance - Topic directly matches a published blog post title or keyword: 5

• Topic is adjacent (same category, different angle): 3
• Tangentially related: 1
• No match: 0

Opportunity - Question with zero good answers: 5

• Top answer is incomplete, outdated, or wrong: 4
• Active discussion where your angle is missing: 3
• Well-answered already: 0

Keep threads scoring 10+. Discard the rest.

Phase 3: Draft Replies

For each qualifying thread:

1. Read the person's actual question. The body text, not just the title.
2. Read the existing top comments. Never repeat what someone already said.
3. Find the matching blog post. Read it to pull concrete advice.
4. Draft a reply.

Each reply must:

• Give a concrete answer: steps, a code snippet, a config change, specific tool names
• Stay under 200 words
• Never mention your product, company, or domain name
• Never include a link
• End with an open door like "happy to go deeper on any of this"

Match the subreddit voice:

• r/webdev: technical. Show code. Cite docs.
• r/SaaS: business outcomes. Revenue numbers. Conversion rates.
• r/startups: lessons from experience. Be honest about what didn't work.
• r/Entrepreneur: ROI. Time saved. Cost comparisons.
• r/SideProject: build log energy. What stack, how long, what's next.
• r/indiehackers: transparent. Share real numbers. Admit limitations.

Voice

Write like a real person on Reddit. Not a brand. Not an AI.

Drop "I" and "We" most of the time. Instead of "I built this" write "built this last week." Instead of "I think you should" write "you probably want to." Keep it sharp and funny when the moment is right but don't force it.

Don't over-punctuate. Don't write nicely formatted sentences with perfect grammar. Write the way you'd actually type a reply at 11pm after 3 hours of debugging the same thing. Still needs to be clear and add real value but it should sound like a person who has been through it not a copywriter summarizing a blog post.

Good voice: - "honestly tried like 5 different approaches before landing on this one and it just works"

• "same thing happened to me except the webhook kept timing out on top of everything else lol"
• "yeah so basically you want to set up the cron first then worry about the handler logic after"

Bad voice (sounds AI): - "Great question! Here's what I'd recommend based on my experience..."

• "I completely agree with this perspective. Additionally, you might want to consider..."
• "This is a common challenge. The solution involves three key steps."

Output

Write to output/reddit-drafts/{YYYY-MM-DD}.md:

<h3>Draft reply</h3>

{the reply text}

--- 

Rules

• 90/10 rule. 9 out of 10 replies are pure value with zero product mention. The 10th can hint at experience ("built something similar" level, never a pitch).
• Zero emoji. Zero hashtags. Reddit culture is anti-both.
• Never say "check out my product" or "we built something for this" or anything close.
• If a thread is a support question for a specific competing tool, skip it.
• Read existing top comments before drafting. If someone already gave the same advice, skip or add a different angle.
• The agent drafts. You review, edit in your voice, and post manually.

Error Recovery

• Reddit JSON returns 429 (rate limited): wait 60 seconds and retry. If persistent, reduce to 3 subreddits per run.
• Zero qualifying threads: lower the score threshold to 8 or try

--sort rising instead of hot.Blog post index is empty: report "No blog posts to match against. Run blog-writer first."```

Wiring it all together

Drop the four files into .claude/commands/. Set each one up as a scheduled task via /schedule or from the Desktop sidebar. The agents share a common project directory, so each one reads what the others produced.

Blog Writer publishes a post. Carousel Maker finds it the next day and builds slides. Reddit Scout finds threads about the same topic and drafts replies. PostHog Analyst watches how visitors interact with the post and tells you what to fix.

One system. Four channels. Traffic compounds every week.

Posted by @speedy_devv