Chase difficulty rating at the innings break — grades how hard a target is (Easy to Very Hard) from historical chase-success data. Pay per call via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| target | Yes | The target to be chased. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses 'pay per call via x402' (a behavioral trait) and describes the grading from historical data, implying a read-only operation. However, it does not explicitly confirm non-destructive behavior or mention any rate limits or permissions, leaving some gaps.
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 consists of two concise sentences. The first sentence front-loads the core purpose and output, and the second adds cost information. Every part is necessary and no words are wasted.
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?
The tool is simple (1 parameter, no output schema). The description explains the output range (Easy to Very Hard) and data source (historical chase-success data), and includes cost info. However, it could be more precise by listing the exact possible grades or stating the return type (string), making it slightly incomplete.
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 coverage is 100% with one parameter 'target' described as 'The target to be chased.' The description adds no extra meaning beyond the schema, such as units (runs) or format constraints. Baseline 3 is appropriate given high schema coverage.
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 it's a chase difficulty rating at innings break, grading from Easy to Very Hard based on historical data. It uses a specific verb 'grades' and resource 'chase difficulty rating', distinguishing it from sibling tools like hsh-cricket-chase-winprob (win probability) and hsh-cricket-first-winprob (first innings win probability).
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 at the innings break, but does not explicitly state when to use this tool versus alternatives (e.g., chase-winprob for probability instead of difficulty). No when-not-to-use or comparison to siblings is provided, only implicit context.
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.
Most tools have distinct purposes, but some closely related tools (e.g., hsh-b2b-*, hsh-esg-* variants) could cause confusion. Descriptions help differentiate, but an agent might still misselect similar products.
Naming convention is mixed: some tools use hyphens (hsh-b2b-contact), others use underscores (hsh_broker_data_request). While mostly readable, the inconsistency could be confusing for agents expecting a uniform pattern.
32 tools is on the high side for a single server, but given its purpose as a data marketplace, the large number reflects a wide catalog. However, it may be overwhelming for agents to navigate.
Covers many data domains but has obvious gaps (e.g., weather, social media). The inclusion of custom data request tools (hsh_describe_data_need, hsh_broker_data_request) mitigates these gaps, allowing agents to request missing data.
