install_snippets
Return ready-to-paste configuration snippets for installing this MCP server in Claude Code, Cursor, Cline, Continue.dev, Windsurf, and Zed. Free.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Predict — Prediction Market Data for AI Agents
TDQS
A4.2/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adequately reveals behavior: returns ready-to-paste snippets for multiple IDEs and notes it's free. No hidden side effects are expected for this read-only tool.
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?
Single sentence, no wasted words. All essential information is front-loaded.
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?
Given no parameters and no output schema, the description covers the tool's purpose and output sufficiently. Minor room for improvement (e.g., format of snippets) but not necessary.
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?
No parameters exist, so baseline score of 4 applies. Description does not need to add parameter semantics.
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 it returns configuration snippets for installing the MCP server in specific IDEs. It is distinct from sibling tools like list_endpoints or pricing_info.
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?
The description implies usage when snippets are needed but does not explicitly state when to use or avoid this tool versus siblings. No alternatives mentioned.
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
A3.5/5.0
Disambiguation3/5
Most tools occupy distinct roles (install, usage stats, wallet setup), but list_endpoints and pricing_info overlap substantially: both report paid endpoints and prices, even though one emphasizes live status and the other detailed fees/payment networks. Descriptions help separate them, but an agent could still pick the wrong one for a pricing question.
Naming Consistency3/5
Names are uniformly snake_case and readable, but the pattern is mixed: install_snippets and list_endpoints use verb_noun, while pricing_info, usage_stats, and wallet_helper use noun-based names. This is a readable mixed convention rather than a chaotic one.
Tool Count3/5
Five tools is a reasonable number for a small server, but for a product called 'Prediction Market Data for AI Agents' the set is oddly scoped: everything is onboarding/pricing/usage meta-tools rather than data tools. The count is not excessive, but it feels thin for the apparent market-data purpose.
Completeness1/5
The server promises prediction market data, yet none of the five tools retrieves markets, odds, prices, positions, or any actual market data. Even if the free helper tools are complete, the core data surface is entirely absent, leaving agents with no way to fulfill the server's stated purpose.