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 Kevin-Liu-01/Agent-Machines --skill content-strategygit clone --depth 1 https://github.com/Kevin-Liu-01/Agent-MachinesWrote 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/kevin-liu-01/agent-machines/content-strategy)<a href="https://agentmods.dev/skills/kevin-liu-01/agent-machines/content-strategy"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/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/kevin-liu-01/agent-machines/content-strategy"><img src="https://agentmods.dev/badge/skills/kevin-liu-01/agent-machines/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 | $0.00069 | $0.00756 |
| Opus 5 | $0.00034 | $0.00378 |
| Sonnet 5 | $0.00014 | $0.00151 |
| Haiku 4.5 | $0.00007 | $0.00076 |
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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Strategy
Positioning Arc
The progression: "talented builder" (early) -> "dangerous early engineer with taste" (mid) -> "operator mode" (mature). Each phase has specific content types and proof requirements.
Content Calendar
Phase 1 (Builder): Dev diary + frontend theses (architecture posts, custom renderers, design system work)
Phase 2 (Taste): Design system work (behavior vs aesthetic control, component library positioning)
Phase 3 (Operator): PMF, agent revenue, conversion, growth loops
Weekly Rhythm
- 5 X posts (3 build logs, 1 take, 1 trend reaction)
- 2 LinkedIn posts (narrative, credibility-building)
- 15-20 meaningful replies across both platforms
- 5 DMs to people whose work connects
- 1 artifact/diagram per week (screenshot, architecture sketch, code snippet)
Four Content Pillars
Build in Public -- prove craft. Dev diaries, custom renderers, design systems, frontend patterns. Reaction: "this person ships ambitious technical work."
Field Notes -- prove applied relevance. SEO/GEO, agent demos, event learnings, growth loops. Reaction: "this person is close to real product usage."
Product and Market Diagnosis -- prove thinking range. PMF, crowded-market strategy, conversion. Reaction: "this person has an original point of view."
Human Context -- sparingly. Hackathon summaries, founder conversations, travel moments with real story. Reaction: "this person is in motion."
Content Mix (per 10 posts)
| Bucket | Share |
|---|---|
| Technical build logs | 5 |
| Product and market lessons | 3 |
| Field notes and human context | 2 |
Quality Gate
- Could only you post this exact thing?
- Is there a concrete proof element?
- Does it teach, reveal, or frame something?
- Is the first line strong enough without baiting?
- Is the close inviting without begging?
- Does it reinforce the target reputation?
If a draft fails checks 1 or 2, kill it or rewrite it.
Capture Schema
For each candidate idea: working title, pillar, one-sentence claim, specific proof, why it matters now, best platform/format, artifact to attach, confidentiality check. If claim, proof, or "why it matters" is missing, the post is not ready.
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.
- 11d ago First seen · 74 lines · 69 tokens per session scan A ff6c20b1ac5e
content-strategy is a skill published in the GitHub repository Kevin-Liu-01/Agent-Machines (29 stars, last pushed yesterday), licensed MIT. It adds 69 tokens to every session and 756 once invoked, about $0.0003 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 2026-08-30.
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