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 OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-content-factorygit clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skillWrote 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/osidemedia/higgsfield-ai-prompt-skill/higgsfield-content-factory)<a href="https://agentmods.dev/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-content-factory"><img src="https://agentmods.dev/badge/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-content-factory/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/osidemedia/higgsfield-ai-prompt-skill/higgsfield-content-factory"><img src="https://agentmods.dev/badge/skills/osidemedia/higgsfield-ai-prompt-skill/higgsfield-content-factory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 166 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00183 | $0.03757 |
| Opus 5.5 | $0.00073 | $0.01503 |
| Sonnet 5.5 | $0.00037 | $0.00751 |
| Haiku 4.5 | $0.00018 | $0.00376 |
Grade A, and why
higgsfield-content-factory 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 3d 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 — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Higgsfield Content Factory — Campaign Orchestration Pipeline
Contents
- 1. Two operating principles
- 2. Onboarding — one message, all buttons, no pauses
- 3. The campaign mix — 5 UGC formats (even split)
- 4. Stage 1 — Trend research & viral ideas
- 5. Stage 2 — Video content plan
- 6. Stage 3 — Generate in Marketing Studio
- 7. Stages 4–5 — Publish & report
- 8. Hard rules (consolidated)
- 9. Source acknowledgment
A 5-stage pipeline that runs a full ad campaign on top of Higgsfield
Marketing Studio: Research → Plan → Generate → Publish → Report. Where
higgsfield-marketing-studio is the engine reference (what the presets,
parameters, hooks, and avatars are), Content Factory is the orchestration
layer that drives a whole campaign turn by turn — researching trends,
planning a dated content calendar, generating in batches, scheduling to ads,
and reporting cost savings.
Translated from Adil Aliyev's higgsfield-content-factory source skill, per
the v3.7.13 / v3.7.16 translation precedent. All Marketing Studio API
ground-truth — preset slugs, parameter schema, hook/setting/avatar handling
— lives in ../higgsfield-marketing-studio/SKILL.md and is NOT restated
here. This sub-skill carries the pipeline scaffolding the marketing-studio
sub-skill deliberately deferred. The publish + cost-report tail (Stages 4–5)
lives in the companion publish-and-report-workflow.md satellite.
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.
- 3d ago Changed · +20 lines 505a3ebabe28
- 1mo ago First seen · 258 lines · 183 tokens per session scan A 8e1c7e1ea80e
higgsfield-content-factory is a skill published in the GitHub repository OSideMedia/higgsfield-ai-prompt-skill (800 stars, last pushed 2d ago), licensed MIT. It adds 183 tokens to every session and 3,757 once invoked, about $0.0007 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 2026-08-30.
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