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 pixelab-ch/higgsfield-skills --skill 11-social-hookgit clone --depth 1 https://github.com/pixelab-ch/higgsfield-skillsWrote 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/pixelab-ch/higgsfield-skills/11-social-hook)<a href="https://agentmods.dev/skills/pixelab-ch/higgsfield-skills/11-social-hook"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/11-social-hook/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/pixelab-ch/higgsfield-skills/11-social-hook"><img src="https://agentmods.dev/badge/skills/pixelab-ch/higgsfield-skills/11-social-hook.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 | $0.00087 | $0.01480 |
| Opus 5.5 | $0.00035 | $0.00592 |
| Sonnet 5.5 | $0.00017 | $0.00296 |
| Haiku 4.5 | $0.00009 | $0.00148 |
Grade A, and why
higgsfield-social-hook 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Social Hook Skill
What this skill does
Crafts scroll-stopping hook video prompts for TikTok, Instagram Reels, and YouTube Shorts and routes them to the best Higgsfield model. On request, it assembles the full parameter set, surfaces the credit cost, and — after explicit user confirmation — generates the asset via the opt-in generation flow.
Model routing
Primary and fallback video models
| kling3_0 (primary) | grok_video (fallback) | |
|---|---|---|
| Rationale | Wide duration range, mode tuning, supports start + end image | Fallback when primary unavailable; native audio |
| Mode | std, pro, 4k* |
No tunable params |
| Sound | on, off |
Native audio (always on) |
| Aspect ratios | 16:9, 9:16, 1:1 |
16:9, 9:16, 1:1 |
| Duration | 3–15 s (continuous range) |
1–15 s (continuous range) |
| Media roles | start_image, end_image |
start_image only (max 1) |
*kling3_0 4k mode is a generation-mode enum, NOT a 4K output-resolution claim.
Do not describe it as 4K video or high-resolution output.
Routing rule: Use kling3_0 by default. Only fall back to grok_video when
(1) the primary model is unavailable, or (2) the user wants native audio generation
and, after being informed of the trade-offs (no tunable params, no end_image,
start_image max 1), explicitly accepts those constraints. Never switch silently.
MODEL-06 directive: If a parameter is rejected at generation time, call
higgsfield:models_explore with the target model name to re-verify the live schema.
Full parameter tables: references/model-specs.md.
Per-platform aspect ratio quick rule
Vertical 9:16 for TikTok / Reels / Shorts; 16:9 for standard YouTube and LinkedIn;
1:1 for Instagram feed square posts (kling3_0 and grok_video both support 1:1).
Full per-platform recommendation table: references/model-specs.md.
Prompt-building workflow
What ships with it
4 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 · 121 lines · 87 tokens per session scan A e159cd41feca
higgsfield-social-hook is a skill published in the GitHub repository pixelab-ch/higgsfield-skills (10 stars, last pushed 5mo ago), licensed MIT. It adds 87 tokens to every session and 1,480 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 2026-08-31.
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