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hsh_broker_data_request

Route a data need through HSH (the data-fulfillment layer for agents). HSH checks its warm inventory first — if a matching product is pre-positioned, you get an immediate-fulfillment quote; otherwise a fresh-fulfillment quote. Use this when you need data mid-task and want HSH to fulfill it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
needYesPlain-language description of the data you need
agent_idNoOptional calling-agent identifier
keywordsNoOptional match keywords (e.g. tickers, topics)
max_price_usdNoOptional budget ceiling in USD

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It explains the warm/fresh inventory check but is ambiguous about whether it returns an actual fulfillment or just a quote. It omits side effects, permissions, rate limits, and error handling, leaving significant gaps.

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

Conciseness5/5

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

Two sentences with no wasted words. The first sentence defines the action, the second adds usage guidance. It is well front-loaded and efficient.

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

Completeness2/5

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

While the description covers the core workflow, it lacks details on output format, error cases, and what happens when no inventory is found. Without an output schema or annotations, the agent may be left guessing about the response structure.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds marginal value by explaining the 'need' parameter as 'plain-language' and 'keywords' with examples, but does not go beyond the schema descriptions.

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

Purpose4/5

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

The description clearly states the tool routes data needs through HSH and explains the warm vs fresh fulfillment distinction. It differentiates from sibling tools by positioning itself as a generic routing tool, though it could be more explicit about when to use specific siblings.

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

Usage Guidelines3/5

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

The description provides clear usage context: 'Use this when you need data mid-task and want HSH to fulfill it.' However, it lacks explicit guidance on when not to use it or references to alternative tools for specific data types.

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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TDQS

B3.3/5.0
Disambiguation4/5

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 Consistency3/5

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.

Tool Count3/5

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.

Completeness3/5

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.