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negotiator402 Negotiation Session
x402
negotiator402 Negotiation Session is a paid API for AI agents from negotiator402.alogos.xyz, paid per call via x402, $10/call, status unknown (last checked 2026-09-15).
Takes a plain-language 2-party negotiation scenario (context, objectives, constraints) and returns a structured negotiation plan with ZOPA, BATNA, concession schedule, decision points, and scenario branches — with LLM-derived guidance flagged as unverified.
Price / call$10
Success—
StatusUnknown
How this service works
Self-evolving strategic reasoning agent — agent-native, pay-per-call: solve 2-player normal-form games (pure & mixed Nash equilibria), formulate plain-language 2-party negotiations into payoff matrices and solve them, and compute optimal second-price/Vickrey auction bids. Unlike a raw LLM endpoint, every answer carries a `verified` trust flag — `verified:true` means a deterministic solver (nashpy / closed-form) computed and confirmed the result, NOT a language model. The formulator layer self-improves training-free from production traffic: every formulation is logged, solver-verified outcomes become reward signals, and the underlying LoRA model is periodically retrained (SFT + RLVR) on its own verified history. No API key, no subscription — agents pay per request via x402 (Base/USDC) or MPP (Tempo/pathUSD).
Output
A structured JSON object containing: a `guidance` block with ZOPA, BATNA, reservation and aspiration values (LLM-derived, inferred); an `offer_plan` with a sequenced offer/counteroffer list, concession schedule, decision points, and scenario branches; a narrative `explanation`; and a `verification` block indicating which components (if any) were solver-verified. The `verified` field will be 'false' for successful sessions (full artifact is LLM-derived, not deterministically verified) or 'refused' on failure. Cost is $10 USDC per call via x402 (Base/USDC) or MPP.
Example use cases
Example prompt
“I need a full negotiation strategy for a software licensing deal — my objective is to get the annual price under $50K with a 3-year contract, my constraints are a hard budget cap of $60K and I can't accept anything shorter than 2 years, and I know the vendor tends to anchor high but values long-term commitments. Can you give me a concession schedule, decision points, and ZOPA analysis?”
Technical details
Endpoint
POSThttps://negotiator402.alogos.xyz/v1/negotiation-sessionWhen to prefer
Use this endpoint when you need a structured, multi-step negotiation plan with concession schedules and scenario branches for a 2-party deal expressed in plain language — especially when you want ZOPA and BATNA framing. Prefer it over a raw LLM prompt when you want a standardized JSON output with explicit verification flags distinguishing solver-backed from inferred results, and when pay-per-call (no subscription) is preferred. For pure game-theory Nash equilibrium or Vickrey auction problems, sibling endpoints on the same host may be more appropriate.
Side effects
- verified: 'refused' returned if the negotiation scenario cannot be formulated or solved
- Malformed input (missing required fields: context, objectives, or constraints) returns a 4xx error
- Ambiguous or extremely sparse context may produce low-quality LLM-derived guidance with no solver-backed components
- Payment failure via x402/MPP blocks the call entirely
- Truncated response schema suggests some output fields may be absent in edge cases
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| contextrequired | string | Description of the negotiation context and background. |
| objectivesrequired | string | Your objectives and desired outcomes. |
| constraintsrequired | string | Your constraints: budget, timeline, red lines, walk-away conditions. |
| offer_history | string | Optional: previous offers/exchanges so far. |
| counterpart_profile | string | Optional: known information about the counterpart (style, preferences, history). |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| guidancerequired | object | |
| verifiedrequired | string | Always 'false' for a successful session because the complete LLM-derived artifact is not deterministically verified; 'refused' on failure. |
| offer_plan | object | |
| explanation | string | Narrative summary of the negotiation plan. Inferred, not solver-backed. |
| verificationrequired | object | |
| opponent_model | object | |
| decision_pointsrequired | object | |
| scenario_branchesrequired | object | |
| concession_schedulerequired | object | |
| solver_backed_components | array | List of components that are solver-backed (vs inferred). Always includes the items actually verified by nashpy/closed-form. |
Tags
x402
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