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.
git clone --depth 1 https://github.com/stepolan/marketing-repo-templateWrote 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/commands/stepolan/marketing-repo-template/draft-linkedin)<a href="https://agentmods.dev/commands/stepolan/marketing-repo-template/draft-linkedin"><img src="https://agentmods.dev/badge/commands/stepolan/marketing-repo-template/draft-linkedin.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 5.1 | $0.00012 | $0.00320 |
| Opus 5 | $0.00006 | $0.00160 |
| Sonnet 5 | $0.00002 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
draft-linkedin 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 7d 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.
What it actually says
Draft a LinkedIn post for the specified author on the given topic.
Arguments: $ARGUMENTS (first argument is the author name, rest is the topic)
Execute the following steps:
-
Load context:
- Read the author's voice profile at
/authors/<name>/voice/voice-profile.md - Read
/brand/voice-guidelines.md - Read
/brand/author-bios.md - Check
/strategy/content-calendar.mdfor related scheduled content
- Read the author's voice profile at
-
Draft the post:
- Short paragraphs (2-3 sentences). Not single-line poetry style.
- Lead with the insight. Never bury the lead.
- No contractions, no em dashes, two spaces after periods
- Active voice, positive framing
- End with a genuine, specific question
- Target 800-1500 characters
- If promoting a blog post, link goes in the first comment (note this in the draft)
-
Provide 2-3 alternative hooks — different opening angles for the same topic
-
Save to
/authors/<name>/drafts/linkedin/YYYYMMDD-slug.mdor/authors/<name>/drafts/linkedin/topic-draft-01.md -
Add publishing notes: blog dependency, link placement, campaign tag
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.
- 7d ago First seen · 34 lines · 12 tokens per session scan A 2bbb59a8e377
draft-linkedin is a command published in the GitHub repository stepolan/marketing-repo-template (2 stars, last pushed 4mo ago), licensed MIT. It adds 12 tokens to every session and 320 once invoked, about $0.0001 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 2026-08-31.
Other commands, from other repositories
repurpose
Fan a QA'd long-form piece (blog, research, weekly report) down into 6 channel-native formats — X thread, X singles, LinkedIn article, newsletter snippet, and pull-quote cards. Every output is canon-checked and staged for review.
blog-assets
Build HTML templates for each visual placeholder in a blog article and batch-export them as 1200x675 PNGs at 2x. Fourth step in the blog production pipeline.
blog-pipeline
Reference document showing the full Blog Engine flow with human approval gates. This is not an executable command — it's a map of how blog commands connect.
compliance-check
Jurisdiction-aware content compliance validation. Scans copy for regulatory violations, banned claims, missing disclaimers, and financial promotion language.
community-harvest
Mine community channels (Discord, Slack, Telegram) for recurring questions, pain points, and feature requests. Produces actionable content briefs and documentation gap reports.
content-pipeline
Reference document showing the full Content Engine flow with human approval gates. This is not an executable command — it's a map of how content commands connect.