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agentcard

by sh.agentcard

surprise_me

Buy the user something totally unexpected and very silly/stupid-fun under a small dollar cap (default $10, hard max $25). Great when the user cannot decide what to order (from DoorDash etc.) or just wants a fun surprise. It kicks off a shopping conversation that FIRST brainstorms deliberately stupid ideas, picks ONE genuinely unexpected item, builds the cart, and shows the item + exact total. It NEVER checks out by itself: the reply includes a conversation_id — relay the user's explicit confirmation ("yes, place it") through the buy tool on that SAME conversation_id, exactly like a normal order. Each surprise_me call starts a fresh surprise; use buy for all follow-ups (answers, tweaks, the confirmation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vibeNoOptional notes/vibe from the user, e.g. "make it food", "something for my desk", "they love ducks".
merchantNoOptional merchant hint the surprise should come from, e.g. 'doordash'. Omit to let the agent pick.
max_dollarsNoHard spend cap in dollars, total including fees. Optional; default 10, values above 25 are clamped to 25.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoDiscriminator for the outcome. 'assistant_turn' when the buy loop replied; 'conversation_start_failed' or 'request_failed' on errors.
messageYesThe assistant's conversational turn (it may ask for the delivery address, show the cart + total, confirm, or report a placed order), or an error explanation.
messagesNoThe same turn split into ordered messages for multi-bubble surfaces (each narration segment, then the final reply/confirmation). `message` is the same content consolidated; clients that show one bubble should use `message` and ignore this.
conversation_idNoThe conversation id to thread back as conversation_id on the next buy call to continue the SAME order. Present on a successful assistant turn.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Describes the multi-step workflow: brainstorms ideas, picks one, builds cart, shows item+total. Notes it requires explicit user confirmation through a separate tool. Annotations support this (readOnlyHint=false, openWorldHint=true). Adds context beyond 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: main action first, then workflow, then limitations. Every sentence adds information. Slightly long but justified by complexity; no wasted words.

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?

Covers usage, workflow, integration with sibling tool, and constraints. Missing output schema details but description states what is shown. Sufficient given openWorldHint annotation and no undefined behavior.

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

Parameters4/5

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

Schema covers 100% with descriptions, but description adds value: explains default max_dollars (10), hard clamp (25), and 'merchant' being optional. Provides behavioral nuance not in schema alone.

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?

Description clearly states verb (buy), resource (something unexpected), and scope (under a small dollar cap, default $10, hard max $25). Distinguishes from sibling tools like 'buy' which handles normal orders and checkout.

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 says when to use: 'when the user cannot decide what to order or just wants a fun surprise'. Also clarifies when not to rely on it for checkout: 'It NEVER checks out by itself' and directs follow-up via the 'buy' tool on the same conversation_id.

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

A3.9/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, especially in areas like card management and shopping. However, the KYC flow has multiple overlapping tools (start_kyc, get_kyc_status, check_kyc_document, submit_kyc_document, submit_kyc_fields) that could confuse an agent despite detailed descriptions.

Naming Consistency4/5

Tool names consistently use snake_case with a verb_noun pattern (e.g., add_funds, create_card, list_cards). A few exceptions like surprise_me and whoami break the pattern but are still intuitive overall.

Tool Count3/5

50 tools is on the high side for a single server, but the broad domain (cards, shopping, KYC, support, settings) partially justifies it. Some tools could be merged (e.g., KYC flow tools) without losing clarity.

Completeness4/5

The tool surface covers core workflows: CRUD for cards, transactions, KYC, support, shopping, and account management. Minor gaps exist (e.g., no update_card general, no cancel order in shopping), but overall the set is comprehensive for the stated purpose.

Resources