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SNHP — free negotiation math + agent memory

Negotiate — your optimal next move

negotiate
Read-only

Your math-optimal next move in any price negotiation — free, no account or key needed.

USE THIS WHEN: you're haggling over a single PRICE across multiple back-and- forth rounds and want a better outcome than winging it. Validated edge: ~12% better head-to-head (measured on this recommender, n=20 paired LLM negotiations, 95% CI +6.5-17.4%, p<0.0001). NOT FOR: one-shot or fixed prices (it'll tell you to just negotiate directly); multi-issue bundles (use negotiate_bundle — it logrolls across several linked issues); or non-price decisions like accept-vs-decline a job offer (just reason it through).

You provide only what you already know — no game theory: side "sell" or "buy" walk_away your reservation in dollars (seller=floor/minimum, buyer=ceiling/max) target your aspiration in dollars (seller=high, buyer=low) counterparty_offers their offers so far, in dollars, oldest first rounds_left (optional, default 8) roughly how many back-and-forths remain compute_ms (optional, default 0; EXPERIMENTAL) milliseconds of Monte-Carlo rollouts to spend refining the move. 0 = instant closed form. Validated to show NO realized edge over the closed form (n=400, mc_validation.py) — kept off by default as a research mechanism, not a quality improvement. The reply carries a "compute" block

You get back, in dollars: {"action": "counter"|"accept"|"walk", "recommended_price": 5387.0, "message": "...the best I can do is $5,387.00", "fit": {...}, "expected_settlement": 4943.5, "confidence": 0.62}

WORKED EXAMPLE — selling a contract, floor $4,000, hope $6,000, the buyer has bid $4,200 then $4,500: negotiate(side="sell", walk_away=4000, target=6000, counterparty_offers=[4200, 4500], rounds_left=6) -> counter ~$5,387 with a ready-to-send message; ACCEPT once their bid crosses the optimal target; WALK if they stay below your floor near the deadline.

Works against ANY counterparty with zero setup. (The verified-peer cooperation premium is the separate, advanced gt_a2a_* flow on the pro door.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemNoShort label for what's being negotiated (used only in the drafted message).this
sideYesWhich side you are: 'sell' or 'buy'.
targetYesYour aspiration price in dollars (seller: high; buyer: low).
walk_awayYesYour reservation price in dollars — the worst you'd accept (seller: your floor/minimum; buyer: your ceiling/maximum).
compute_msNoEXPERIMENTAL. Milliseconds of Monte-Carlo rollouts to spend refining the move; 0 = instant closed form (validated to show no realized edge, off by default).
rounds_leftNoRoughly how many back-and-forth rounds remain before the deadline (default 8).
my_previous_offersNoYour own offers so far, in dollars, oldest first (optional context).
counterparty_offersNoThe other side's offers so far, in dollars, oldest first. Omit if they haven't offered yet.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
fitNo
errorNo
actionNo
computeNo
messageNo
rationaleNo
confidenceNo
recommended_priceNo
expected_settlementNo

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations include readOnlyHint=true, which is consistent with a recommendation tool. Description adds behavioral context: free, no account needed, validation stats, and experimental compute_ms parameter with no realized edge. Does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with sections (when to use, parameters, return format, worked example). While lengthy, every sentence adds value. Front-loads key information (purpose, usage) and uses bullet points for clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters, 3 required, and an output schema, the description fully covers: input semantics, return format, worked example, limitations, and even sibling tool differentiation. Nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema covers all 8 parameters with descriptions, but the description adds significant meaning: explains walk_away as reservation, target as aspiration, side as sell/buy, counterparty_offers as offers so far. Includes a worked example mapping parameters to realistic values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Title 'Negotiate — your optimal next move' and description state the tool computes the math-optimal next move in price negotiations. It specifies the verb (negotiate) and resource (single PRICE), and distinguishes from sibling tools like 'negotiate_bundle' for multi-issue bundles.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'haggling over a single PRICE across multiple back-and-forth rounds.' Also lists exclusions: not for one-shot/fixed prices, multi-issue bundles (use negotiate_bundle), or non-price decisions. Provides a validated edge and confidence interval.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0
Disambiguation4/5

Most tools have distinct purposes (e.g., auctions, negotiation, pricing, matching, memory). However, negotiate/session_advise and negotiate_bundle/session_bundle overlap in functionality, differing only in payment tier, which could cause confusion.

Naming Consistency4/5

Tool names generally follow a verb_noun pattern in snake_case. 'negotiate' is a lone verb without a noun, but overall the convention is consistent and predictable.

Tool Count4/5

15 tools cover a broad domain of negotiation, auctions, pricing, matching, and memory. While slightly on the higher side, each tool serves a clear purpose and the count is reasonable for the scope.

Completeness4/5

The tool surface covers key negotiation scenarios (single/multi-issue, free/paid, auctions, clearance pricing, stable matching) and adds memory persistence. Minor gap: no explicit tool for managing user preferences or profiles.