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UCF v2 Identity Compiler
x402
UCF v2 Identity Compiler is a paid API for AI agents from unlike-tale-plays-rose.trycloudflare.com, paid per call via x402, $0.5/call, status unknown (last checked 2026-09-13).
Compiles a structured persona pack (name, axioms, voice, constraints) into a ready-to-use system prompt for AI agents
Price / call$0.5
Success—
StatusUnknown
How this service works
UCF v2 Identity Compiler — persona pack in, system prompt out
Output
A compiled system prompt string derived from the provided persona pack — incorporating the agent's name, behavioral axioms, voice style, constraints (never-do rules), operator context, and session task — ready to be injected as a system message into an LLM interaction.
Example use cases
Customer support agent persona deployment
“Build me a system prompt for a customer support persona named 'Nova' — her axioms are 'be empathetic' and 'resolve issues in one turn', her voice is 'warm and direct', she should never 'escalate without trying a fix first' or 'use technical jargon', and the operator is 'ShopEasy' with the role of 'frontline support agent'.”
Content moderation bot identity setup
“Compile a system prompt for a moderation agent called 'Guardian' with axioms 'enforce community guidelines' and 'assume good intent first', voice style 'neutral and firm', never 'shame users' or 'make final bans without review', operator is 'ForumHub' in the role of 'trust and safety operator', task is 'reviewing flagged posts' on a 'forum' platform.”
Research assistant persona for enterprise LLM
“I need a compiled system prompt for a research persona named 'Lumen' — axioms are 'cite primary sources', 'acknowledge uncertainty', and 'prioritize peer-reviewed data', voice is 'academic and precise', it should never 'speculate as fact' or 'omit confidence levels', operator is 'ResearchCo' with role 'analyst', model is 'gpt-4o', task is 'literature summarization'.”
Technical details
Endpoint
POSThttps://unlike-tale-plays-rose.trycloudflare.com/v1/compileWhen to prefer
Choose this endpoint when you need to programmatically generate structured, consistent system prompts from modular persona definitions — especially useful in multi-agent pipelines, persona management systems, or platforms where different operators deploy different agent identities at scale. Prefer this over hand-crafting system prompts when you want deterministic, schema-driven prompt assembly with operator and session context baked in.
Side effects
- Missing required persona fields (name, axioms, voice, never) returns a validation error
- Axioms array outside 2–4 item bounds causes schema rejection
- Missing operator name or role results in an incomplete compilation or error
- Malformed JSON body returns a 400-level error
- Service unavailability on the ephemeral Cloudflare tunnel returns a 5xx or connection timeout
- Payment failure via x402 protocol blocks the request before compilation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| persona | object | |
| session | object | |
| operator | object |
Tags
x402
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