Bellwether
Server Details
Live Kalshi + Polymarket prediction-market data and cross-venue arbitrage spreads, one schema.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3/5 across 3 of 3 tools scored.
Each tool has a distinct purpose: get_market retrieves a single market, list_markets returns a collection, and matching_markets finds cross-venue matches. No overlap or ambiguity exists.
All tool names follow a clear verb_noun pattern in snake_case: get_market, list_markets, matching_markets. The pattern is consistent and predictable.
With only 3 tools, the set is on the smaller side but appropriate for a focused domain. It covers the essential operations without being overly sparse.
The tools cover core read operations (get one, list all, find matches) but lack filtering or search capabilities. Minor gaps exist, but the primary use case is well-served.
Available Tools
3 toolsget_marketBInspect
Get one normalized market. venue is 'kalshi' or 'polymarket'.
| Name | Required | Description | Default |
|---|---|---|---|
| venue | Yes | ||
| market_id | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether the tool is read-only, error handling for missing markets, or any side effects. It only states that the output is a 'normalized market' without further detail.
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 extremely concise with two short sentences, containing no redundant or irrelevant information. Every word serves a purpose.
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 simplicity of the tool (2 parameters, no output schema), the description is minimally adequate but lacks completeness. It does not explain the return format, error states, or how this tool fits with siblings. More context would improve the agent's understanding.
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?
The description adds meaning for the 'venue' parameter by indicating allowed values, which is not present in the schema (0% coverage). However, it does not clarify the format or constraints for 'market_id', so the added value is partial.
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 'Get one normalized market' which is a specific verb+resource. It also specifies the allowed venue values 'kalshi' or 'polymarket', distinguishing it from sibling tools that likely operate on multiple markets or have different query mechanisms.
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?
No guidance is given on when to use this tool versus its siblings list_markets or matching_markets. The description only includes a constraint on venue values but does not explain prerequisites, alternatives, or context for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_marketsBInspect
List open prediction markets across Kalshi and Polymarket (normalized).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| venue | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It does not mention whether the tool fetches live data, caching, sorting, pagination, or side effects, leaving the agent unaware of important behavioral traits.
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 concise sentence that efficiently states the tool's purpose. However, it could include more detail without sacrificing conciseness.
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?
Despite having an output schema and sibling tools, the description is too brief to be complete. It lacks details about limitations, output structure, or how parameters influence results, making it insufficient for an agent to fully understand the tool.
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%, and the description does not explain the parameters (limit, venue) at all. No information about accepted values, constraints, or how they affect the output.
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 verb (list), the resource (open prediction markets), and the scope (across Kalshi and Polymarket, normalized). It distinguishes from sibling tools 'get_market' (single market retrieval) and 'matching_markets' (matching functionality).
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 listing open markets but does not explicitly state when to use or avoid this tool, nor does it mention alternatives or context for its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
matching_marketsCInspect
Find the same real-world event on both venues, with the YES price spread.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| threshold | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full weight but only states the tool finds matches with a price spread. It does not disclose which venues are supported, whether results are sorted, if authorization is needed, or any side effects. This is insufficient for safe invocation.
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 concise sentence that front-loads the core action. However, it lacks structure for parameter details or usage examples, though it efficiently communicates the primary function.
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?
Despite having an output schema, the description does not explain what data is returned (e.g., market IDs, spreads) or how the two parameters affect the results. For a tool with 0% schema coverage, this is incomplete and leaves essential context missing.
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%, and the description entirely omits the two parameters ('limit' and 'threshold'). Without explanation of their purpose or default values, an agent cannot correctly configure or understand their effect.
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 finds the same real-world event on both venues with the YES price spread, using a specific verb and resource. It distinguishes itself from siblings 'get_market' (single market details) and 'list_markets' (listing markets) by focusing on cross-venue matching.
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?
No guidance is given on when to use this tool versus alternatives like 'get_market' or 'list_markets'. There is no mention of prerequisites, when not to use it, or how it compares to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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