Paid data plan required. Return every active Polymarket market across all categories, not only crypto. AI execution credits do not unlock this export. The text result is one LLM-readable line per market: MARKET_NAME | OUTCOME PRICES | DEADLINE | MARKET_ID. The sweep fails closed if complete pagination cannot be verified and includes timestamp, count, source-page count, and SHA-256.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, openWorldHint), the description adds critical behavioral details: paid plan requirement, credit restriction, output format (LLM-readable lines with specific fields), and pagination fail-closed with SHA-256 verification.
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 concise, with every sentence adding essential information, and key constraints are front-loaded.
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 zero parameters, no output schema, and annotations present, the description fully covers purpose, constraints, output format, error behavior, and verification, making it complete for the tool's functionality.
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?
No parameters exist, so the description does not need to add parameter details. Baseline 4 applies, and the description compensates by detailing the return format.
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 states it returns every active Polymarket market across all categories, distinguishing it from sibling tools like polymarket_search_markets and polymarket_get_market.
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 description explicitly mentions the paid data plan requirement and that AI credits do not unlock the export, providing clear context for when to use. It does not explicitly exclude alternatives, but the purpose contrasts with sibling tools.
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.
Each tool has a distinct purpose, clearly separated by venue prefix (kalshi_, limitless_, polymarket_) and action (get_orderbook, get_snapshots, search_markets). The screener and whoami tools are unique and not overlapping with any other tool.
Most tools follow the venue_verb_noun pattern (e.g., kalshi_get_orderbook, polymarket_get_snapshots). However, polymarket_all_markets uses 'all' instead of a verb, and screener/whoami deviate entirely from the pattern, causing minor inconsistency.
With 12 tools covering three venues plus cross-venue and session info, the count is well-scoped. Each tool serves a clear role without unnecessary bloat or deficiency.
The tool surface covers the core data retrieval operations (orderbook, snapshots, search, single market) for all venues. Missing are update/delete operations but those are outside the data provider scope. A minor gap is the lack of a dedicated 'get_market' for Kalshi and Limitless, though search_markets provides similar info.
