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 skeletorflet/opencode-supreme-setup --skill fal-generategit clone --depth 1 https://github.com/skeletorflet/opencode-supreme-setupWrote 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/skeletorflet/opencode-supreme-setup/fal-generate)<a href="https://agentmods.dev/skills/skeletorflet/opencode-supreme-setup/fal-generate"><img src="https://agentmods.dev/badge/skills/skeletorflet/opencode-supreme-setup/fal-generate/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/skeletorflet/opencode-supreme-setup/fal-generate"><img src="https://agentmods.dev/badge/skills/skeletorflet/opencode-supreme-setup/fal-generate.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 | $0.00289 |
| Opus 5 | $0.00016 | $0.00144 |
| Sonnet 5 | $0.00007 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
fal-generate 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 6d 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.
What it actually says
fal-generate
Curated from the fal.ai community team.
What it does
Generate images and videos using fal.ai AI models. Production-grade catalogue covering Flux, SDXL, ideogram, and other community-hosted endpoints.
Source
- Upstream: https://github.com/fal-ai-community/skills
- Category:
image-generation
How to use
This catalogue entry advertises the skill in Open Design so the agent discovers it during planning. To run the full upstream workflow with its original assets, scripts, and references, install the upstream bundle into your active agent's skills directory:
# Inspect the upstream README for exact paths
open https://github.com/fal-ai-community/skills
Then ask the agent to invoke this skill by name (fal-generate) or with
one of the trigger phrases listed in this skill's frontmatter.
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.
- 6d ago First seen · 44 lines · 33 tokens per session scan A dd7b016b4e01
fal-generate is a skill published in the GitHub repository skeletorflet/opencode-supreme-setup (47 stars, last pushed 3mo ago), licensed MIT. It adds 33 tokens to every session and 289 once invoked, about $0.0002 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 2026-09-03.
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