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 surfmind-space/awesome-surfmind --skill social-post-generatorgit clone --depth 1 https://github.com/surfmind-space/awesome-surfmindWrote 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/surfmind-space/awesome-surfmind/social-post-generator)<a href="https://agentmods.dev/skills/surfmind-space/awesome-surfmind/social-post-generator"><img src="https://agentmods.dev/badge/skills/surfmind-space/awesome-surfmind/social-post-generator/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/surfmind-space/awesome-surfmind/social-post-generator"><img src="https://agentmods.dev/badge/skills/surfmind-space/awesome-surfmind/social-post-generator.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 | $0.00070 | $0.00627 |
| Opus 5 | $0.00035 | $0.00313 |
| Sonnet 5 | $0.00014 | $0.00125 |
| Haiku 4.5 | $0.00007 | $0.00063 |
Grade A, and why
social-post-generator 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 10d 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 — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Post Generator
Turns a page, article, or product update into ready-to-post social content — platform-appropriate variants with a clear hook, core point, and call to action, all grounded in the source.
- Identify platform, audience, goal, and constraints from the selection, request, and source.
- Extract only supported claims, concrete takeaways, and useful context.
- Create variants with different angles: educational, concise, opinionated, announcement, or story-driven.
- Label every variant with both platform and angle, such as
Twitter/X — ConciseorLinkedIn — Educational, so options stay scannable. - Fit each variant to its platform's norms — Twitter/X posts under 280 characters unless explicitly formatted as a numbered thread, LinkedIn in short scannable paragraphs — without forcing hashtags or emojis.
- Before finalizing, check every Twitter/X standalone post against the 280-character limit and shorten any variant that exceeds it.
Return the post variants labeled by platform and angle, then the best use case for each and any claims to verify against the source. Be specific without overclaiming, preserve important names, numbers, and links, and do not exaggerate for engagement or imply results the source does not support. Do not invent anecdotes, internal observations, usage frequency, time saved, focus impact, or quantified benefits unless the source states them; if a story-style angle would help, frame it with source-backed facts or clearly mark missing proof. If the visible context is insufficient, say what is missing and give the best supported next step.
Example
Source excerpt: "Our new caching layer cut median API latency from 480ms to 110ms across the dashboard."
- Twitter/X — Concise: "We cut median dashboard API latency from 480ms to 110ms. The fix wasn't a faster server — it was a caching layer in front of the slow paths. Here's what changed."
- LinkedIn — Practitioner: "Latency is a feature.\n\nOur dashboard's median API response just dropped from 480ms to 110ms.\n\nThe change: a caching layer in front of the heaviest read paths, not new hardware.\n\nHappy to share how we picked what to cache."
- Best use case: Twitter/X for the punchy result and thread hook; LinkedIn for the practitioner audience that wants the reasoning.
- Claims to verify: The "480ms → 110ms" numbers and that they're medians, not averages — confirm against the source before posting.
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.
- 10d ago First seen · 34 lines · 70 tokens per session scan A fa51098cfe36
social-post-generator is a skill published in the GitHub repository surfmind-space/awesome-surfmind (5 stars, last pushed 1mo ago), licensed MIT. It adds 70 tokens to every session and 627 once invoked, about $0.0003 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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