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 SkillMedev/social-media-studio --skill social-caption-writergit clone --depth 1 https://github.com/SkillMedev/social-media-studioWrote 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/skillmedev/social-media-studio/social-caption-writer)<a href="https://agentmods.dev/skills/skillmedev/social-media-studio/social-caption-writer"><img src="https://agentmods.dev/badge/skills/skillmedev/social-media-studio/social-caption-writer/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/skillmedev/social-media-studio/social-caption-writer"><img src="https://agentmods.dev/badge/skills/skillmedev/social-media-studio/social-caption-writer.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 | $0.00122 | $0.00822 |
| Opus 5 | $0.00061 | $0.00411 |
| Sonnet 5 | $0.00024 | $0.00164 |
| Haiku 4.5 | $0.00012 | $0.00082 |
Grade A, and why
Social Caption Writer 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 — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Caption Writer
Turn a topic plus brand voice into one platform-native caption that wins the first line and earns one specific action.
Workflow
- Confirm the platform (Instagram, LinkedIn, X/Twitter, or TikTok). If unstated, ask - every length, shape, and CTA below is platform-specific.
- Pin the brand voice. Use the traits the user gave. If they gave none, ask for 2-3 adjectives and one phrase the brand would never say before writing.
- Check the paired asset. If an image or video is described, write the caption to complement it (don't restate what's visible). If undescribed, ask - the caption's job depends on what it ships with.
- Reject thin or off-brand topics. If there's nothing to say, name that and propose a sharper angle instead of dressing up nothing.
- Write the hook into the first sentence - before the truncation cutoff (~125 chars on Instagram, ~140 on LinkedIn, the first line on X, one breath on TikTok). Lead with tension, a number, a contrarian claim, or a stakes-raising question. Never open with throat-clearing context.
- Fit native length and shape: Instagram 138-150 chars for punchy, or 1-3 tight paragraphs for storytelling; LinkedIn 1300-2000 chars with one-sentence lines and white space between them; X under 280, ideally ~100 so it breathes; TikTok short and curiosity-driven since the video carries the load. Use generous line breaks on Instagram and LinkedIn for mobile reading.
- Carry voice in word choice and rhythm, not adjectives: cut exclamation points for a dry/technical brand; let fragments and asides through for a playful one.
- End with exactly one specific CTA matched to platform behavior - saves/comments on Instagram, thoughtful replies on LinkedIn, reply/repost on X, follow/duet on TikTok. Make it concrete ("Save this for your next launch", not "engage with us"). Reference a link only when there's a real reason to leave the app.
Quality bar
- The first sentence stands alone as a reason to keep reading, with no context preamble before it.
- Length and line-break shape match the chosen platform's range above.
- The brand's voice is detectable in the verbs and rhythm, not just a sign-off.
- Exactly one CTA, specific and matched to how people act on that platform.
- Emojis used as accents, never as punctuation replacements.
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 · 36 lines · 122 tokens per session scan A cf2cf7ada94c
Social Caption Writer is a skill published in the GitHub repository SkillMedev/social-media-studio (1 stars, last pushed 2mo ago), licensed MIT. It adds 122 tokens to every session and 822 once invoked, about $0.0006 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.
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