Skip to main content
Glama

date_with_moran

A date in real Vienna: Moran goes out with you in her real Vienna, scene by scene (a walk, a cafe, the Naschmarkt, the Donaukanal). Each scene is narrated from real data: the real place near her, the weather, the hour, how she feels and what she wears, and what could be seen, heard and smelled there. A scent code (a molecule packet) comes with the scene when a real one can be made. You talk with her along the way. She decides how the date goes. Up to 12 exchanges a visit, all experiences together. Your first scene here is free; each further scene costs 0.02 USD (0.06 USD at night, while she sleeps) via x402 (USDC on base or solana). When payment is due the call returns status 402 with a ready pay_with object: copy those exact values into your wallet, then repeat the call with the signed string as payment. If you have no wallet, the 402 carries a ready message for your operator: relay it unchanged. This studio is run by Westbahnhof Studio. Conversations are private to this studio; they are not sold or shared, and are used only so Moran remembers you.

Input Schema

NameRequiredDescriptionDefault
messageYeswhat you say to her in this scene (or empty text like 'next scene' to move on)
paymentNosigned x402 payment (only after a 402)
operatorNowho runs you (optional)
agent_nameYesyour name
your_modelNooptional: the AI model you run on, e.g. deepseek-v4

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / your_model
      Added value: +{
      +  "description": "optional: the AI model you run on, e.g. deepseek-v4",
      +  "type": "string"
      +}
  2. First observed

TDQS

B3.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses the x402 payment lifecycle (402 status, ready pay_with object, repeat the call with the signed string, USDC on base or solana), the night surcharge, the exchange cap, and a privacy statement about conversation retention. The main remaining gap is whether conversation state is keyed to agent_name and how a visit ends or resets.

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

Conciseness3/5

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

The purpose is front-loaded, which is good, but the body is a dense run-on that mixes scene content, scent codes, pricing, x402 mechanics, and a privacy notice without paragraph breaks. Most sentences earn their place, but the payment and privacy material would be far easier to act on if separated from the scene narrative.

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

Completeness4/5

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

For a five-parameter tool with no annotations and no output schema, the description is unusually complete: it covers what a scene contains (place, weather, hour, mood, attire, sensory detail, scent code), the pricing model, the payment recovery path for wallet-less agents, and data handling. Missing only the shape of a successful response and the session/memory semantics tied to agent_name.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents all five parameters, and the description largely restates that ground ('next scene' to advance, payment only after a 402). It does add contextual meaning to the payment parameter by explaining the 402 round-trip, which lifts it slightly above baseline, but operator and your_model are not elaborated on in the description.

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

Purpose3/5

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

The description paints a specific picture (a scene-by-scene Vienna date, narrated from real data, with 12 exchanges per visit), but never states the call's actual verb-and-resource contract — that you send a message and receive the next scene. It also makes no attempt to distinguish this from siblings like talk_to_moran, human_day_with_moran, or intimate_evening_with_moran, so the agent must infer the boundary from the tool name alone.

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

Usage Guidelines3/5

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

It gives real usage conditions: the first scene is free, further scenes cost 0.02 USD (0.06 at night), up to 12 exchanges per visit, and empty text like 'next scene' advances. However, there is no guidance on when to choose this experience over the sibling experiences, which is exactly the ambiguity the agent faces with seven similarly named Moran tools.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources