Call this to fetch the live bids and asks orderbook depth for a Kalshi market ticker (e.g. 'KXFED-25JUN-H') or Polymarket YES-token ID.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker_or_token | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full load for behavioral disclosure. It describes the action ('fetch live bids and asks orderbook depth') but does not state side effects (none expected), authentication needs, rate limits, or data freshness guarantees. The term 'live' is ambiguous—it could imply real-time or just current snapshot.
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 a single, well-structured sentence that immediately states the tool's purpose and key details. Every clause adds value, with no redundancy or fluff. The action verb ('fetch') is 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 the tool's low complexity (one parameter, no nested objects, with output schema), the description covers the essential inputs and outputs. It mentions both supported exchanges and the return type ('bids and asks orderbook depth'). The output schema is present but not described, which is acceptable as per rubric. Slightly penalized for missing behavioral details (e.g., live vs cached data).
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 0% (the parameter 'ticker_or_token' has no description in the schema), so the description must compensate. It explains that the parameter accepts a Kalshi market ticker or Polymarket YES-token ID and gives examples. However, it does not specify format requirements (e.g., case sensitivity, full naming conventions) beyond the examples, leaving some ambiguity.
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 the tool's purpose: to fetch live bids and asks orderbook depth. It specifies the resource (orderbook depth) and provides concrete examples of supported identifiers ('KXFED-25JUN-H' for Kalshi, Polymarket YES-token ID), making it unambiguous and distinct from sibling tools.
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 includes a call-to-action ('Call this to...') but provides no guidance on when to use this tool versus sibling tools like foresea_recent_trades or foresea_edge_board. No alternatives or exclusions are mentioned, which limits decision support.
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.
Some tools have overlapping purposes: foresea_edge_board and foresea_scan_markets both return markets ranked by model-vs-market edge, and foresea_forecast vs foresea_debate_market both provide probabilities for a question. Descriptions help differentiate (specific vs. broad, quick vs. deep) but the boundaries are not always clear.
All tools share the 'foresea_' prefix and use lowercase with underscores, which provides consistency. However, the remainder mixes verb-noun phrases (analyze_market, scan_markets) with bare nouns (orderbook, price_history) and compound nouns (market_leaderboard, polymarket_meta), creating minor stylistic inconsistency.
17 tools is slightly above the typical well-scoped range of 3-15, but the server covers a broad domain (forecasting, market analysis, data feeds, portfolio optimization, track record). A couple of tools are redundant (edge_board vs scan_markets) and could be consolidated, but overall the count is reasonable.
The tool set covers the core analytics workflow: general forecasting, specific market analysis, opportunity scanning, market data (quotes, orderbook, history, trades), portfolio allocation, and performance evaluation. Minor gaps exist (e.g., no tool for detailed market rules or user portfolio tracking), but these are likely outside the intended scope.
