{"ok":true,"host":"rng.sociologic.ai","status":"failed","manifest":{"positioning":"This host serves agents and applications that require verifiable, cryptographically secure randomness on demand. It covers three common primitive types — unique identifiers, floating-point values, and bounded integers — each generated via rejection sampling to eliminate bias. It is not a streaming or subscription randomness service; it is a stateless, per-request API suited for discrete randomness needs with an audit trail.","host_overview":"rng.sociologic.ai provides cryptographically secure random value generation via three endpoints: UUID v4 identifiers, random floats in [0,1), and random integers within a caller-specified range. Each endpoint returns entropy proof (raw bytes and hex) alongside the generated value(s), enabling auditability of the randomness source. Pricing is per-call, with UUID generation priced at $0.01 per UUID.","routing_guidance":"Use this host when an agent needs cryptographically secure, auditable random primitives — specifically UUID v4 identifiers, bounded integers, or floats in [0,1) — and requires entropy proof for each value. Do not use it for UUID versions other than v4, random byte arrays, random strings, or values outside the supported output types; those require a different host. It is not suitable for high-frequency or bulk randomness (beyond 100 UUIDs per request) due to per-call pricing, and it offers no streaming or subscription mode. For non-cryptographic pseudorandom needs where cost or throughput matters more than auditability, a local PRNG library is a better fit.","capability_clusters":[{"skill_names":["generate-uuid-v4"],"cluster_name":"Unique Identifier Generation","cluster_summary":"Produces one or more UUID v4 values backed by cryptographic entropy, suitable for record keys, session tokens, and correlation IDs."},{"skill_names":["fetch-random-float","fetch-random-integer"],"cluster_name":"Cryptographic Random Primitives","cluster_summary":"Generates unbiased random floats in [0,1) and random integers within a caller-defined inclusive range, both with entropy proof via rejection sampling."}],"cross_skill_workflows":[{"steps":[{"skill_name":"fetch-random-integer","description":"Generate an unbiased random index within [0, list_length-1] to select an item from a collection."},{"skill_name":"fetch-random-float","description":"Generate a random float to apply a probability threshold check (e.g., acceptance/rejection in weighted sampling or Monte Carlo validation)."}],"when_to_use":"Use when an agent needs to select a random item from a list by first picking a random index and optionally validating the draw with a float-based probability check.","workflow_name":"Seeded Lottery or Weighted Sampling"}]},"model":"claude-sonnet-4-6","version_no":2,"generated_at":"2026-05-06T10:30:18.261Z","provenance":"ai_authored_unreviewed","ai_authored":true,"merchant_reviewed":false,"merchant_edited":false,"merchant_reviewed_at":null,"merchant_edited_at":null,"skill_md_url":"https://x402gle.com/servers/rng.sociologic.ai/SKILL.md","skills_url":"https://x402gle.com/servers/rng.sociologic.ai/skills.json"}