fal-platform

A skill for Fal Platform APIs, which manage AI models and track their prices and usage. It provides general guidance and patterns for those tasks.

In plain words
What is it for?
Use it when managing models or working with Fal Platform pricing and usage-tracking APIs.
Why use it?
It gives a defined scope for working with model management, pricing, and usage data while noting that environment-specific checks are still needed.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/beel-collab/presets.dev/fal-platform
Any agent
npx skills add beel-collab/presets.dev --skill fal-platform
Clone the repo
git clone --depth 1 https://github.com/beel-collab/presets.dev

Made for: Claude Code, Codex.

Per session 11 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 223 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00011 $0.00223
Opus 5 $0.00005 $0.00112
Sonnet 5 $0.00002 $0.00045
Haiku 4.5 $0.00001 $0.00022

Measured 3d ago against content hash df9c9ef47771, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

fal-platform 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.

claude/skills/ai-ml/fal-platform/SKILL.md · 30 lines

What it actually says

Fal Platform

Overview

Platform APIs for model management, pricing, and usage tracking

When to Use This Skill

Use this skill when you need to work with platform apis for model management, pricing, and usage tracking.

Instructions

This skill provides guidance and patterns for platform apis for model management, pricing, and usage tracking.

For more information, see the source repository.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Changes

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.

  1. 3d ago First seen · 30 lines · 11 tokens per session scan A df9c9ef47771

Subscribe to this mod's changes

fal-platform is a skill published in the GitHub repository beel-collab/presets.dev (2 stars, last pushed 3mo ago), licensed MIT. It adds 11 tokens to every session and 223 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 2026-08-31.

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