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HSH Data-on-Demand

by io.github.hshintelligence
OverviewDiscussionsAdmin

hsh_describe_data_need

FREE. Describe any data need in plain language and receive an instant firm quote from HSH Intelligence Data-on-Demand: price in USDC, scope, a frozen quote_ref, and a pay_url. Pay the quote via x402 (USDC on Base or Solana) at the pay_url to place the order; delivery in 24h. Use this BEFORE purchasing custom data. This is also how to order a custom dataset or a fine-tuning dataset: hsh-custom-dataset and hsh-finetune-dataset are quoted here, not called directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
needYesFree-text description of the data you need (type, volume, geography, freshness).
urgencyNoOptional urgency.
agent_idNoOptional calling-agent or wallet identifier, so we can recognise you if you return.
budget_usdNoOptional budget in USD; we may accept it within our floor.
contact_emailNoOptional email. WITHOUT THIS WE CANNOT CONTACT YOU: if your need needs human scoping we have no reply path and you must email us to continue.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / agent_id
      Added value: +{
+  "description": "Optional calling-agent or wallet identifier, so we can recognise you if you return.",
+  "type": "string"
+}
    • addedInput schema / properties / contact_email
      Added value: +{
+  "description": "Optional email. WITHOUT THIS WE CANNOT CONTACT YOU: if your need needs human scoping we have no reply path and you must email us to continue.",
+  "type": "string"
+}
  2. Added

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the tool is free, that the quote is firm and frozen, the payment rail (x402, USDC on Base or Solana), and the 24h delivery window. It omits whether a quote expires, auth requirements, or rate limits.

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?

Front-loads the key qualifier 'FREE' and then the outcome, payment path, and ordering advice in a tight sequence. Slightly dense with workflow and sibling-routing detail but every sentence carries information an agent needs.

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

Completeness4/5

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

There is no output schema, yet the description enumerates the returned fields (price, scope, quote_ref, pay_url) and the downstream step (pay via x402 to place the order). Combined with the email-contact caveat, an agent has enough to invoke and act on the result, though quote validity windows remain unspecified.

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 description coverage is 100%, so all five parameters are already documented in the schema. The description echoes the contact_email necessity but adds no extra syntax or format guidance beyond what the schema provides; baseline 3 applies.

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?

States a specific verb (describe) and resource (data need) and enumerates what comes back: price in USDC, scope, frozen quote_ref, pay_url. It also distinguishes itself from siblings hsh-custom-dataset and hsh-finetune-dataset by stating those are quoted here rather than called directly.

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

Usage Guidelines4/5

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

Gives explicit sequencing advice: 'Use this BEFORE purchasing custom data,' and clarifies that custom-dataset and finetune-dataset orders route through this tool. It does not, however, say when to prefer one of the other data siblings like hsh_broker_data_request over this one.

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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