Call this to retrieve historical price series or OHLC candlesticks for a market (e.g. Kalshi ticker or Polymarket token/slug).
| Name | Required | Description | Default |
|---|---|---|---|
| series_ticker | No | ||
| ticker_or_market | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states 'retrieve' which suggests a read operation, but does not disclose any behavioral details such as data range limits, pagination, rate limits, or authentication requirements. The description adds the concept of OHLC candlesticks, but lacks depth for a tool without annotation support.
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 with no extraneous content. It is front-loaded and efficient.
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 presence of an output schema and two parameters, the description is too brief. It does not explain the output format, the difference between the two parameters, or how this tool fits with historical data needs. With many sibling tools, more context would be beneficial.
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%, meaning the description does not document any parameters. The description mentions 'ticker_or_market' in examples but does not explain the 'series_ticker' parameter or clarify how the two parameters interact. With zero schema descriptions, the description fails to add sufficient meaning.
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 retrieves historical price series or OHLC candlesticks for a market, with concrete examples (Kalshi ticker, Polymarket slug). This distinguishes it from real-time data tools like foresea_live_data, though not explicitly. The verb 'retrieve' and resource 'price history' are specific.
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 implies use for historical data but provides no explicit guidance on when to prefer this over sibling tools like foresea_analyze_market or foresea_scan_markets. It does not exclude any use cases or mention 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.
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.
