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 jeremylongworth-source/AgentSkills --skill social-asset-productiongit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/social-asset-production)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/social-asset-production"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/social-asset-production/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/jeremylongworth-source/agentskills/social-asset-production"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/social-asset-production.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00079 | $0.00614 |
| Opus 5.5 | $0.00032 | $0.00246 |
| Sonnet 5.5 | $0.00016 | $0.00123 |
| Haiku 4.5 | $0.00008 | $0.00061 |
Grade A, and why
social-asset-production 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 1mo 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Asset Production
Core Workflow
- Identify platform, placement, audience, asset purpose, dimensions, required text, brand assets, source images, distribution context, and review owner.
- Verify current platform specs when exact size, crop, file type, or upload behavior matters.
- Choose the right production approach: generated bitmap, deterministic image composition, editable vector, screenshot, thumbnail, or post-production edit.
- Design for the smallest real use: circular profile crop, mobile feed, banner overlap, thumbnail preview, or compact article card.
- Export useful variants with clear names. Prefer PNG for text/logo-heavy assets and JPG for photo-heavy feed or banner assets unless platform guidance differs.
- Review legibility, crop safety, contrast, brand fit, platform constraints, accessibility, and provenance before marking the asset ready.
Asset Checks
- Text fits at mobile size and does not sit on crop edges.
- Profile assets survive circular crop and small thumbnail display.
- Banner assets account for profile photo overlap and responsive cropping.
- Post images carry one clear message and do not depend on tiny body copy.
- Video covers still read with platform UI overlays.
- File names include brand, placement, size, and variant when possible.
Freshness Rule
Platform dimensions and crop behavior change often. Before giving exact sizes for X, Facebook, LinkedIn, YouTube, Instagram, TikTok, or other social surfaces, verify current official docs when practical.
Read references/social-asset-checklist.md when preparing platform-specific
exports, profile/banner assets, or crop-safe review notes.
Safety Rules
- Do not use private likenesses, third-party logos, copyrighted characters, protected artwork, or confidential source assets without rights and review.
- Do not claim an AI-generated or edited asset is original, licensable, or platform-compliant without human review.
- Preserve source files or prompts when useful for provenance and iteration.
- Do not upload or publish assets unless the user explicitly asks and account access supports it.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 69 lines · 79 tokens per session scan A 9bf9b4f74b2f
social-asset-production is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 17d ago), licensed MIT. It adds 79 tokens to every session and 614 once invoked, about $0.0003 per session on Opus 5.5. 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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