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 skills/robinsadeghpour/content-workflow/generate-contentnpx skills add robinsadeghpour/content-workflow --skill generate-contentgit clone --depth 1 https://github.com/robinsadeghpour/content-workflowWrote 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/robinsadeghpour/content-workflow/generate-content)<a href="https://agentmods.dev/skills/robinsadeghpour/content-workflow/generate-content"><img src="https://agentmods.dev/badge/skills/robinsadeghpour/content-workflow/generate-content.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 | $0.00063 | $0.01448 |
| Opus 5 | $0.00032 | $0.00724 |
| Sonnet 5 | $0.00013 | $0.00290 |
| Haiku 4.5 | $0.00006 | $0.00145 |
Grade B, and why
generate-content scanned grade B with 1 finding 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
The orchestrator handles everything: research pass, track selection, repo-screenshot dispatch, writer/critic loops, slide rendering via the two new skills, and DB writes. You do NOT run any scripts directly here. How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
generate-content — Full Pipeline Content Generation
One command turns a kept idea into platform-native drafts across 4 channels, with critic review applied before Robin sees anything.
Usage
/generate-content <idea_id>
<idea_id> — UUID of a kept idea from data/content.db.
What It Does
- Read the kept idea from
data/content.db(must havestatus = 'kept'). - Research pass (D-06) — produces a structured brief at
data/research/<idea_id>.mdvia NotebookLM. Cached on re-runs. Setsresearch_thinflag if sparse. - Pick slide track —
brandedorpersonal, fromidea.visual_approachor inferred from the idea title. - Repo screenshot pre-flight — if the idea references a GitHub repo, the
repo-screenshotsubagent captures a clean PNG of the repo card for use as animage-overlayslide. - Per platform: spawn
writer→ runcriticloop → render slides → save draft.- TikTok EN, TikTok DE: writer produces a
slides_specfor the chosen track. Rendered viagenerate-branded-slidesorgenerate-personal-slides. - Instagram: writer produces a caption only. Slides reuse TikTok EN PNGs (cropped if personal track).
- LinkedIn: always branded. Writer produces a post text + branded
slides_spec. Rendered viagenerate-branded-slides.
- TikTok EN, TikTok DE: writer produces a
- Save drafts to
data/content.dbwithstatus = 'critic_approved'. - Report the summary table to Robin.
Implementation
Spawn the content-orchestrator agent:
Agent(content-orchestrator):
"Generate content for idea <idea_id>."
The orchestrator handles everything: research pass, track selection, repo-screenshot dispatch, writer/critic loops, slide rendering via the two new skills, and DB writes. You do NOT run any scripts directly here.
Present the orchestrator's summary output to Robin when it completes.
Output to Robin
Content generation complete for idea: <idea_id> — "<title>"
Track: <branded|personal> Repo screenshot: <yes|no>
Platform | Slides | Critic | Draft ID
------------- | --------------------- | ----------------- | --------
TikTok EN | personal N slides | critic_approved | <uuid>
TikTok DE | personal N slides | critic_approved | <uuid>
Instagram | reuses TikTok EN | critic_approved | <uuid>
LinkedIn | branded N slides | critic_approved | <uuid>
Files: media/output/<idea_id>/
Next: /approve to review and schedule.
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 · 122 lines · 63 tokens per session scan B ca4104383fd2
generate-content is a skill published in the GitHub repository robinsadeghpour/content-workflow (55 stars, last pushed 3mo ago), licensed MIT. It adds 63 tokens to every session and 1,448 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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