Conduct an adversarial multi-agent debate (Bull vs. Bear vs. Chief Risk Judge) to cross-examine evidence and isolate blind spots on a forecasting question.
| Name | Required | Description | Default |
|---|---|---|---|
| platform | No | Market | |
| question | Yes | ||
| market_probability | No | ||
| resolution_criteria | No |
| 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 carries the full burden for behavioral disclosure. It only describes the action but omits any side effects, permissions, rate limits, or whether the tool is read-only or mutating. For a multi-agent debate tool, it is unclear if it makes external calls, requires authentication, or has costs. The description fails to disclose these behavioral traits beyond the basic action.
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, front-loaded sentence that packs the action, roles, and purpose without any wasted words. It is concise and well-structured, prioritizing the core functionality.
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 complexity (multi-agent debate) and the presence of 4 parameters with zero documentation, the description is incomplete. It does not explain parameter semantics, behavioral traits, or how the debate is structured. Although an output schema exists (covering return values), it does not compensate for the missing guidance on inputs and operational behavior. The description is insufficient for a tool with such nuanced inputs.
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 explains none of the parameters. It only references a 'forecasting question' which maps to the 'question' parameter, but this adds no meaning beyond the schema itself. It does not clarify 'market_probability', 'resolution_criteria', or 'platform' defaults (e.g., 'Market'), leaving agents without understanding of how to use these fields.
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 action ('Conduct an adversarial multi-agent debate') and its purpose ('cross-examine evidence and isolate blind spots'), with specific roles (Bull, Bear, Chief Risk Judge) that distinguish it from sibling tools like foresea_analyze_market or foresea_forecast. The verb+resource is specific and unambiguous.
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 usage for forecasting questions but does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or mention any sibling tools. It offers context about the target domain but lacks direct guidance on when to prefer it over other analysis or forecasting 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.
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.
