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phara23

@alpha-arcade/mcp

by phara23

stream_orderbook

Stream real-time orderbook snapshots for any prediction market via WebSocket, returning bids, asks, spread, and per-side details using the market slug.

Instructions

Get a real-time orderbook snapshot for a market via WebSocket. Faster than on-chain reads (~5s vs ~10s). Returns the same full processed snapshot shape as get_full_orderbook, with bids, asks, spread, and per-side YES/NO detail. Requires the market slug (URL-friendly name), not the market app ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe market slug (URL-friendly name, e.g. "will-btc-hit-100k")
timeoutMsNoMax time to wait for a snapshot in ms (default: 15000)
Behavior3/5

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

With no annotations, the description must disclose behaviors. It mentions WebSocket, real-time, speed, and return shape. But it is ambiguous whether the connection streams updates or provides a single snapshot. The tool name 'stream' suggests continuous, but description says 'snapshot'. It does not mention authentication, rate limits, or what happens on timeout. Transparency is adequate but not complete.

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

Conciseness5/5

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

The description is three short sentences, each adding distinct information: purpose, performance comparison, and return shape plus input requirement. No wasted words; front-loaded with the core action.

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 tool with 2 params and no output schema, this description covers key behavioral aspects (WebSocket, speed, return shape reference) and input semantics. It relies on the user knowing get_full_orderbook's output, but the summary list of fields (bids, asks, spread, YES/NO) provides sufficient context. The ambiguity about streaming vs snapshot keeps it from a 5.

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 coverage is 100%, so baseline is 3. The description adds value by explaining 'slug' is the URL-friendly market name (not app ID), clarifying its usage. It does not add details for 'timeoutMs' beyond schema. This extra context justifies a 4.

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?

The description clearly states the tool's purpose: 'Get a real-time orderbook snapshot for a market via WebSocket.' It specifies the return shape and differentiates from the sibling get_full_orderbook by noting same shape but faster via WebSocket. The verb 'Get' and resource 'orderbook snapshot' are specific and unambiguous.

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

Usage Guidelines4/5

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

The description provides context for when to use this tool: 'Faster than on-chain reads (~5s vs ~10s)' and states it returns the same data as get_full_orderbook, implying use when speed is needed. It also clarifies the input requirement: 'Requires the market slug...not the market app ID.' However, it does not explicitly exclude alternatives or specify when not to use it, missing a full guide.

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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