Recently-listed markets (new contracts) on Kalshi and Polymarket. For finding fresh trading opportunities.
| Name | Required | Description | Default |
|---|---|---|---|
| hours | No | Lookback hours (default 24) | |
| limit | No | Max rows | |
| venue | No | kalshi or polymarket | |
| minLiquidity | No | Minimum liquidity threshold |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden of behavioral disclosure. It tells what the tool returns (recently-listed markets) but does not disclose important traits such as whether results are combined across venues, how 'recently' is defined, ordering, pagination, authentication needs, or any limitations. This is a significant gap for a retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—two brief clauses that immediately convey the core purpose. There is no wasted wording, and the most important information (what the tool returns) is front-loaded. It exemplifies efficient, targeted writing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema and no annotations, the description should explain what the returned market data looks like (e.g., symbols, prices, liquidity fields) to enable correct invocation. It does not, and it also omits any detail about how the venue and lookback parameters affect the results. While the schema covers parameter names, the overall description leaves too much unspecified for a tool with four optional parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all four parameters (hours, limit, venue, minLiquidity) are already documented. The description adds no extra parameter-level context beyond the generic 'fresh' opportunity framing, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the resource (recently-listed markets, new contracts) and the venue scope (Kalshi and Polymarket), which distinguishes it from sibling tools like get_markets. However, it lacks an explicit verb like 'list' or 'returns'; the action is implied by the tool name and the noun phrase structure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'For finding fresh trading opportunities' implies a use case, giving some context for when to use the tool. Yet it provides no explicit guidance on when to use it over alternatives (e.g., get_markets, scan_markets) nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have overlapping purposes, such as multiple market query tools (scan_markets, screen_markets, get_market_detail, get_market_diff, get_market_history, inspect_ticker) and legislative tools (legislation, get_legislation, list_legislation, query_gov). Aliases like get_heartbeat_config/get_heartbeat_status and explore_public/explore_theses add further confusion. An agent would struggle to select the correct tool without deeply reading each description.
Most tools follow a verb_noun pattern (get_, list_, create_, update_), but there are notable deviations: 'legislation' lacks the 'get_' prefix, 'stt' and 'tts' are acronyms, 'monitor_the_situation' is a full phrase, and 'x_account/x_news/x_volume' use a non-standard prefix. The overall style is readable, but the mixed conventions reduce predictability.
108 tools is extreme for any server, even one covering prediction markets, trading, portfolio management, forum, skills, and speech. The massive surface area overwhelms agents and makes the server feel more like a platform than a coherent toolkit. This many tools inevitably leads to redundancy and maintenance burden.
The server covers an impressively broad domain: market data, thesis management, intents, strategies, positions, portfolio, forum, skills, legislative and economic queries, and audio/visual processing. Minor gaps exist (e.g., no delete for skills/theses, no update for some portfolio items) but core workflows are well-supported. Overall lifecycle coverage for most entities is strong.
