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Glama

Prediction Markets

browse_prediction_markets

Browse prediction markets from Polymarket and Manifold. Filter by category (crypto, politics, sports, economics, science, entertainment, pop-culture) or search by keyword.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoKeyword search
tagNoCategory filter (crypto, politics, sports, economics, science, entertainment, pop-culture)
limitNoNumber of results (default 20, max 50)
sourceNopolymarket, manifold, or all (default: all)all

Schema Changelog

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

  1. First observed

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'browse' which implies a read operation, but does not explicitly state read-only behavior, rate limits, response structure, or pagination. Basic disclosure only.

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?

Two clear, front-loaded sentences with no wasted words. The main action and key filters are stated first.

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

Completeness3/5

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

Given 4 optional parameters, no output schema, and no annotations, the description provides a reasonable overview but lacks details on response format, pagination, or usage constraints. Adequate for a browsing tool, but gaps remain.

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 description coverage is 100%, baseline 3. The description adds value by listing the possible categories for the tag parameter and explaining the source parameter options (polymarket, manifold, all). This contextualizes the parameters beyond the schema.

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 verb 'browse', the resource 'prediction markets', and the specific sources 'Polymarket and Manifold'. It also mentions filtering by category or keyword, which distinguishes it from sibling tools that likely focus on details or trends.

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 for browsing/filtering but does not explicitly state when to use this tool versus alternatives like get_market_details or get_trending_predictions. No exclusion criteria or prerequisites are given.

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
Disambiguation5/5

Each tool has a clearly distinct purpose: browsing markets with filters, getting detailed information on a specific market, and fetching trending markets. There is no functional overlap.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case: browse_prediction_markets, get_market_details, get_trending_predictions.

Tool Count5/5

Three tools is appropriate for a focused server covering browsing, details, and trending. The scope is well-defined without being too sparse or bloated.

Completeness4/5

The set covers the core information retrieval needs: discover, examine, and see trends. A minor gap is historical data or outcome timelines, but for a lightweight server this is reasonable.

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