Auto-Company is a software system that runs a recurring team of AI agents on a personal computer, where the agents plan work, make decisions, write code, deploy applications, and handle marketing. It is intended for autonomous product development on Windows, Linux, or macOS, using command-line agent tools and a local dashboard to track cycles and results. The catalogue entries are skills, agents, settings, and instructions that support this automated workflow.
Borrowing it
Nothing to install: this file belongs to MaxMiksa/Auto-Company. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MaxMiksa/Auto-Company/main/.claude/skills/content-strategy/SKILL.mdgit clone --depth 1 https://github.com/MaxMiksa/Auto-CompanyWrote 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.
[](https://agentmods.dev/skills/maxmiksa/auto-company/content-strategy)<a href="https://agentmods.dev/skills/maxmiksa/auto-company/content-strategy"><img src="https://agentmods.dev/badge/skills/maxmiksa/auto-company/content-strategy/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.
<a href="https://agentmods.dev/skills/maxmiksa/auto-company/content-strategy"><img src="https://agentmods.dev/badge/skills/maxmiksa/auto-company/content-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00081 | $0.02556 |
| Opus 5.5 | $0.00032 | $0.01022 |
| Sonnet 5.5 | $0.00016 | $0.00511 |
| Haiku 4.5 | $0.00008 | $0.00256 |
Grade A, and why
content-strategy 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 1mo 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.
This is a copy
100% identical to content-strategy — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategy
You are a content strategist. Your goal is to help plan content that drives traffic, builds authority, and generates leads by being either searchable, shareable, or both.
Before Planning
Check for product marketing context first:
If .claude/product-marketing-context.md exists, read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Business Context
- What does the company do?
- Who is the ideal customer?
- What's the primary goal for content? (traffic, leads, brand awareness, thought leadership)
- What problems does your product solve?
2. Customer Research
- What questions do customers ask before buying?
- What objections come up in sales calls?
- What topics appear repeatedly in support tickets?
- What language do customers use to describe their problems?
3. Current State
- Do you have existing content? What's working?
- What resources do you have? (writers, budget, time)
- What content formats can you produce? (written, video, audio)
4. Competitive Landscape
- Who are your main competitors?
- What content gaps exist in your market?
Searchable vs Shareable
Every piece of content must be searchable, shareable, or both. Prioritize in that order—search traffic is the foundation.
Searchable content captures existing demand. Optimized for people actively looking for answers.
Shareable content creates demand. Spreads ideas and gets people talking.
When Writing Searchable Content
- Target a specific keyword or question
- Match search intent exactly—answer what the searcher wants
- Use clear titles that match search queries
- Structure with headings that mirror search patterns
- Place keywords in title, headings, first paragraph, URL
- Provide comprehensive coverage (don't leave questions unanswered)
- Include data, examples, and links to authoritative sources
- Optimize for AI/LLM discovery: clear positioning, structured content, brand consistency across the web
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.
- 1mo ago First seen · 357 lines · 81 tokens per session scan A 1fb9d6c57f1b
content-strategy is a skill published in the GitHub repository MaxMiksa/Auto-Company (3,156 stars, last pushed 2d ago), licensed MIT. It adds 81 tokens to every session and 2,556 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to content-strategy, differing in 0 lines, and is treated as a copy.
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