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.
npx skills add seb1n/awesome-ai-agent-skills --skill content-strategygit clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skillsWrote 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/seb1n/awesome-ai-agent-skills/content-strategy)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/content-strategy"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/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/seb1n/awesome-ai-agent-skills/content-strategy"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/content-strategy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.02042 |
| Opus 5 | $0.00023 | $0.01021 |
| Sonnet 5 | $0.00009 | $0.00408 |
| Haiku 4.5 | $0.00005 | $0.00204 |
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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- content-strategy — 95% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategy
This skill enables an AI agent to build a comprehensive content strategy from the ground up or audit and improve an existing one. The agent defines content pillars aligned to business objectives, maps content types to funnel stages (TOFU/MOFU/BOFU), creates editorial calendars, and establishes a measurement framework. The output is a repeatable system for producing, distributing, and optimizing content that drives traffic, engagement, and conversions.
Workflow
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Audit existing content and define goals. Inventory all current content assets — blog posts, landing pages, case studies, videos, whitepapers — with their publication dates, traffic, and conversion metrics. Identify top performers, underperformers, and content gaps. Align the strategy to 2–3 measurable goals such as "increase organic traffic 40% in 6 months" or "generate 200 MQLs per month from content."
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Research the target audience and build personas. Define 2–4 buyer personas with demographics, job roles, pain points, content consumption habits, and preferred channels. Map each persona to their buyer journey stages: awareness (problem recognition), consideration (evaluating solutions), and decision (selecting a vendor). This determines what content types each persona needs at each stage.
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Establish content pillars and topic clusters. Define 3–5 content pillars — broad themes that align with the product's value proposition and audience needs. Under each pillar, plan a cluster of 8–15 supporting pieces that link back to a comprehensive pillar page. This structure builds topical authority for SEO and creates a logical content architecture.
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Build the editorial calendar. Plan content production on a rolling 3-month horizon. For each piece, specify the topic, target keyword, content format (blog, video, infographic, podcast), funnel stage, assigned persona, distribution channels, author, and publish date. Balance content across pillars and funnel stages — roughly 60% TOFU, 30% MOFU, and 10% BOFU.
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.
- 9d ago First seen · 91 lines · 45 tokens per session scan A aae99f111048
content-strategy is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 2,042 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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