Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/OSideMedia/higgsfield-ai-prompt-skillnpx agentmods add commands/osidemedia/higgsfield-ai-prompt-skill/validateWrote 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/commands/osidemedia/higgsfield-ai-prompt-skill/validate)<a href="https://agentmods.dev/commands/osidemedia/higgsfield-ai-prompt-skill/validate"><img src="https://agentmods.dev/badge/commands/osidemedia/higgsfield-ai-prompt-skill/validate/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/commands/osidemedia/higgsfield-ai-prompt-skill/validate"><img src="https://agentmods.dev/badge/commands/osidemedia/higgsfield-ai-prompt-skill/validate.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 | $0.00014 | $0.00068 |
| Opus 5 | $0.00007 | $0.00034 |
| Sonnet 5 | $0.00003 | $0.00014 |
| Haiku 4.5 | $0.00001 | $0.00007 |
Grade A, and why
validate 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- validate — 100% identical, 2 lines differ
What it actually says
Run the validation script and report results:
python3 scripts/validate.py
If any checks fail, list each failure with its file path and what needs fixing. If all checks pass, confirm the repo is release-ready.
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.
- 9d ago First seen · 12 lines · 14 tokens per session scan A eba6a8f06728
validate is a command published in the GitHub repository OSideMedia/higgsfield-ai-prompt-skill (514 stars, last pushed 17d ago), licensed MIT. It adds 14 tokens to every session and 68 once invoked, about $0.0001 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 2026-08-30.
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