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 agentmods add skills/ericrisco/rsc-harness/falnpx skills add ericrisco/rsc-harness --skill falgit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/fal)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/fal"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/fal.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.02276 |
| Opus 5 | $0.00039 | $0.01138 |
| Sonnet 5 | $0.00016 | $0.00455 |
| Haiku 4.5 | $0.00008 | $0.00228 |
Grade A, and why
fal scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
description: "Use when calling a fal.ai endpoint by id to generate image, audio, or video from JS/Python/curl: subscribe vs submit, queue states, ED25519 webhook signature verification, per-call cost, or migrating off @f How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fal
The wire to fal.ai's fast, pre-warmed media endpoints: call a model by id, control the queue, get the file back. fal is the fast-media path — latency-optimized image (FLUX, Seedream, SD), audio (TTS, music), and video (Veo, Wan, Kling, Hailuo) endpoints you invoke by id with FAL_KEY.
You own the mechanics: auth, call mode, queue states, webhook signatures, file I/O, per-call cost.
When NOT to use
| You want… | Go to |
|---|---|
| Which model / what to generate / art direction / multi-provider media pipeline | ai-media |
The same kind of models on Replicate (replicate.run / predictions) |
replicate — images-specifically replicate-images |
| Renting a raw GPU pod you SSH into to train or custom-serve | runpod |
| Deploying your own Python function as an autoscaling endpoint | modal |
| Cheap hosted LLM text/chat completions | together-fireworks |
| The generic provider-agnostic webhook receiver/verifier pattern | webhooks |
Rule: if you are not invoking a fal endpoint id with FAL_KEY, you are in the wrong skill.
Setup & auth
# JS — current client. NOT @fal-ai/serverless-client (deprecated, migrate).
npm i @fal-ai/client # latest 1.10.1
# Python
pip install fal-client
export FAL_KEY="key_id:key_secret"
import { fal } from "@fal-ai/client";
// Reads FAL_KEY from env automatically; or set it explicitly:
fal.config({ credentials: process.env.FAL_KEY });
Rule: never ship FAL_KEY to a browser bundle. Proxy every call through your own server. Why: a key in client-side JS lets anyone drain your account — fal endpoints bill per call with no per-request cap.
Pick a call mode
All three modes hit the same queue. Choose by how long the job runs and where you call it from.
| Situation | Mode | Why |
|---|---|---|
| Need the result now, can block, single short job (image, short TTS) | subscribe |
Submits + auto-polls until done; feels synchronous, no polling code |
| Long job (video), batch, or running in a serverless/edge handler that can't hold a connection | submit + webhook_url (or poll) |
Returns a request_id instantly; result arrives later, no held connection |
| Trivially short call, you accept no queue control | run |
Direct synchronous call — no status, no logs; drops on long jobs |
What ships with it
5 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.
- 3d ago First seen · 197 lines · 78 tokens per session scan A b67a8b70a8bd
fal is a skill published in the GitHub repository ericrisco/rsc-harness (65 stars, last pushed yesterday), licensed MIT. It adds 78 tokens to every session and 2,276 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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