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 agentmods add rules/thatrebeccarae/claude-marketing/content-workflowgit clone --depth 1 https://github.com/thatrebeccarae/claude-marketingWrote 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/rules/thatrebeccarae/claude-marketing/content-workflow)<a href="https://agentmods.dev/rules/thatrebeccarae/claude-marketing/content-workflow"><img src="https://agentmods.dev/badge/rules/thatrebeccarae/claude-marketing/content-workflow.svg" alt="Measured on agentmods" 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 | $0.00047 | $0.01908 |
| Opus 5 | $0.00023 | $0.00954 |
| Sonnet 5 | $0.00009 | $0.00382 |
| Haiku 4.5 | $0.00005 | $0.00191 |
Grade A, and why
content-workflow 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 5d 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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Workflow
End-to-end content creation pipeline: research, draft, review, distribute.
Pipeline Stages
Stage 1: Research
Gather raw material for the content piece.
- Topic research — web search, RSS feeds, industry sources
- Source assessment — credibility, recency, relevance
- Data extraction — key statistics, quotes, data points
- Counter-arguments — opposing views, nuance, caveats
- Angle development — what makes this piece unique
Output: Research brief with sources, data points, and recommended angle.
Stage 2: Draft & Edit
Create and refine the content.
- Draft — write following the content type framework and brand voice
- Editorial review against quality criteria:
- Voice consistency
- Structural quality (hook → body → CTA)
- SEO optimization (if applicable)
- Factual accuracy (all claims sourced)
- Readability (appropriate level for audience)
- Revision — apply specific feedback
- Final review — verify all issues addressed
Output: Polished draft ready for approval.
Stage 3: Distribute
Adapt the finished piece for cross-platform distribution.
- LinkedIn post — hook, body, CTA, hashtags
- Twitter/X thread — numbered tweets, hooks per tweet
- Email subject lines — 3 options with preview text
- Pull quotes — 3-5 shareable excerpts for social
Output: Distribution pack with platform-specific adaptations.
Usage Modes
Full Pipeline
/content-workflow [topic]
Runs all 3 stages: research → draft → review → distribute.
Start from Draft
/content-workflow --from-draft [file path]
Skips research. Takes an existing draft through editorial review and distribution.
Distribution Only
/content-workflow --distribute [file path]
Takes a finished, approved piece and creates the social distribution pack.
Content Types
| Type | Research Depth | Draft Length | Distribution |
|---|---|---|---|
| Blog post | Deep (5+ sources) | 1,500-2,500 words | LinkedIn + Twitter + Email |
| LinkedIn post | Light (2-3 sources) | 150-300 words | Twitter adaptation only |
| Twitter thread | Light (1-2 sources) | 5-12 tweets | LinkedIn adaptation only |
| Newsletter | Medium (3-5 sources) | 500-1,000 words | Twitter + LinkedIn teasers |
| Essay | Deep (8+ sources) | 2,000-4,000 words | Full distribution pack |
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.
- 5d ago First seen · 263 lines · 47 tokens per session scan A 82301366c93e
content-workflow is a cursor rule published in the GitHub repository thatrebeccarae/claude-marketing (130 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 1,908 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 2026-08-30.
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