Animica Random Pick

x402

Animica Random Pick is a paid API for AI agents from animica.dev, paid per call via x402, $0.001926/call, status unknown (last checked 2026-10-30).

Randomly selects k items from a candidate list using verifiable DRNG-based randomness, with optional weighting and replacement

Price / call$0.001926

Seller volume →—

Success—

StatusUnknown

How this service works

Animica Python Cloud: deploy a Python function to animica.dev, get a public endpoint, and earn ANM every time someone runs it. Free AI (OpenAI-compatible, no key), free scheduled Workers, and an 80/20 developer split.

Output

Returns a JSON object containing: 'picked' (the selected items, omitted if indices_only=true), 'indices' (0-based positions of picks), 'k' (count picked), 'replace' flag, 'weighted' flag, 'randomness' (DRNG seed/output), 'source', 'health', 'attestation', 'verification', and 'derivation' (rules, steps, optional recompute instructions) — plus payment metadata for the x402 micropayment.

Example use cases

Raffle winner selection

“I have 500 raffle entries in this array — pick 5 winners without replacement and give me verifiable proof of the random draw so entrants can trust it.”

Weighted giveaway draw

“Run a weighted random pick from these prize tiers: ['Grand Prize','Second Prize','Third Prize','Consolation'] with weights [1,3,10,50] — pick 1 winner and show me the randomness attestation.”

Random A/B test assignment

“I need to randomly assign 10 user IDs from this list of 200 to a test group — pick 10 without replacement and return just their indices so I can map back to my dataset.”

Technical details

Endpoint

POSThttps://animica.dev/x402/random/pick?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need cryptographically verifiable, auditable random selection — not just any pseudorandom pick. The DRNG-backed attestation and derivation steps make it suitable for public lotteries, giveaways, or any scenario where participants must be able to independently verify the fairness of the draw. Prefer it over a local random function when auditability, reproducibility via request_id, or weighted sampling is required.

Side effects

items array empty or exceeds 10000 entries — request rejected
k exceeds items.length when replace=false — invalid parameter error
weights array length does not match items array — rejected
float values in weights — rejected (integers only)
response body exceeds 4MB cap (especially with replace:true and large items) — use indices_only:true
Payment of 0.006731 USDC not provided or insufficient — 402 Payment Required

Input

Schema · Request body

Field	Type	Description
k	integer	how many to pick, 1..1000 (default 1; alias count). Without replacement k <= items.length
items	array	candidates, 1..10000 entries (any JSON values)
replace	boolean	true = with replacement (an item can win twice); default false
weights	array	one non-negative INTEGER weight per item (floats rejected: the cumulative search must be recomputable exactly)
request_id	string	your own tag; mixed into the DRNG seed
indices_only	boolean	omit the picked items and return only their 0-based indices — use it when the items are large: the response cap is 4000000 bytes and with replace:true the same item can be emitted k times

Output

Schema · Response

{
  "type": "json"
}

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