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Glama

Foresea Forecasting

by ink.foresea

foresea_scan_markets

Call this when the user wants to find mispriced or interesting markets, not evaluate a specific one. Good triggers: "What should I bet on?", "Find me trading opportunities", "Which markets are mispriced right now?", "What's Foresea's best edge today?", "Scan Polymarket for opportunities". Returns markets ranked by model-vs-market disagreement, each with model probability, market price, and edge. For a specific market, use foresea_analyze_market instead. Example: platform="kalshi", min_edge=0.1 → [{question, market_probability, model_probability, edge, market_url}].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNo
min_edgeNo
platformNopolymarket
evidence_top_kNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It describes the return format (model probability, market price, edge) and includes an example output, implying a read-only operation. However, it does not explicitly state non-destructiveness or any safety aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear purpose, trigger list, output description, and example. It is concise but could be slightly tighter by removing redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters and no annotations, the description provides adequate context for usage and output but lacks parameter documentation. The output schema exists but its content is unknown; the description covers the gist of the return fields.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description only mentions platform and min_edge in an example, leaving limit, query, and evidence_top_k unexplained. With low coverage, the description should add meaning for all parameters, but it does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool finds mispriced or interesting markets, with specific trigger phrases and a distinction from evaluating a specific market. Names the sibling tool foresea_analyze_market as the alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to use (user wants to find trading opportunities) and when not to (evaluating a specific market, directs to foresea_analyze_market). Provides example triggers and a sample invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Foresea Forecasting toolsInspect
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TDQS

A3.6/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count4/5

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.

Completeness4/5

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.

Resources