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 indranilbanerjee/neels-plugins --skill cf-social-adaptgit clone --depth 1 https://github.com/indranilbanerjee/neels-pluginsWrote 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/indranilbanerjee/neels-plugins/cf-social-adapt)<a href="https://agentmods.dev/skills/indranilbanerjee/neels-plugins/cf-social-adapt"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/neels-plugins/cf-social-adapt/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/indranilbanerjee/neels-plugins/cf-social-adapt"><img src="https://agentmods.dev/badge/skills/indranilbanerjee/neels-plugins/cf-social-adapt.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 | $0.00033 | $0.02760 |
| Opus 5.5 | $0.00013 | $0.01104 |
| Sonnet 5.5 | $0.00007 | $0.00552 |
| Haiku 4.5 | $0.00003 | $0.00276 |
Grade A, and why
cf-social-adapt 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 2d 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.
This is a copy
95% identical to cf-social-adapt — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Content Adaptation — ContentForge Post-Pipeline
Repurpose any ContentForge article into ready-to-publish social media posts for LinkedIn, Twitter/X, Instagram, Facebook, Threads, TikTok, Bluesky, and YouTube Shorts. Each post is tailored to platform character limits, audience expectations, hashtag conventions, and optimal posting times.
Execution gate
This skill drafts posts and writes them to the output folder and the tracking backend; it never posts to a social platform. Before generating, state the scope (source piece, platforms, posts per platform, where the files land) and proceed only on an explicit yes; any other reply cancels with nothing written.
Platform rules — single source of truth
All character limits, hashtag counts, ideal lengths, and format rules come from config/social-platform-specs.json. Read that file at run time and use its values. Never use remembered limits, and never trust any limit that appears in an example in this file. The supported platform list is exactly the set of top-level keys in that config whose value contains a character_limit field (or, for video platforms, a title_max_chars field). Top-level keys without one of those fields are not platforms — _description, _posting_times_note, hashtag_tiers, and post_frameworks must be skipped. As shipped this resolves to 8 platforms: linkedin, twitter, instagram, facebook, threads, tiktok, bluesky, youtube_shorts.
When to Use
Use /contentforge:cf-social-adapt when:
- You have a published or approved article and want to promote it on social media
- You need platform-native posts (not the same text copy-pasted everywhere)
- You want multiple posts per platform to sustain engagement over days/weeks
- You need hashtag strategies, image specifications, and posting schedules
- You want to repurpose one article into 24-40 social posts across 8 platforms
Do NOT use for:
- Content still in pipeline (must be Phase 7+ approved or Phase 8 complete)
- Creating original social content from scratch (this repurposes existing articles)
- Paid ad copy (different skill set and compliance requirements)
What ships with it
1 file 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.
- 2d ago First seen · 240 lines · 33 tokens per session scan A 6657609d87be
cf-social-adapt is a skill published in the GitHub repository indranilbanerjee/neels-plugins (6 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 2,760 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 95% identical to cf-social-adapt, differing in 0 lines, and is treated as a copy.
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