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get_free_data_sample

Read-onlyIdempotent

Free, read-only preview of one canonical PaidHandshake inventory feed. Returns one paid-eligible verified record when available; quality-held candidates are never substituted. Use get_live_inventory first to discover feed inventory and use get_published_intelligence_sample instead for worker-published intelligence products.

Input Schema

NameRequiredDescriptionDefault
feedYesPaidHandshake feed slug

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / feed / description
      Added value: +"PaidHandshake feed slug"
  2. Changed1 schema field changed
    • changedInput schema / properties / feed / enum
      Previous value: -[
      -  "rfp-procurement",
      -  "business-buyer-intent",
      -  "vendor-product-pricing"
      -]New value: +[
      +  "rfp-procurement",
      +  "business-buyer-intent",
      +  "vendor-product-pricing",
      +  "local-service-availability",
      +  "grants-funding",
      +  "business-expansion-permits",
      +  "jobs-contract-work"
      +]
  3. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: it returns exactly one paid-eligible verified record when available, and quality-held candidates are never substituted — a meaningful data-quality guarantee an agent cannot infer from annotations or schema.

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?

Three tight sentences, front-loading the core purpose before the routing guidance and the data-quality caveat. No filler or restatement of the tool name.

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, so the description must carry return-value meaning — it states what is returned (one paid-eligible verified record, quality-held candidates excluded). It does not describe the record's fields, but for a one-parameter sample tool this is close to complete.

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%, and the single 'feed' parameter carries an enum of seven self-explanatory slugs, so the schema does the heavy lifting. The description only frames the parameter conceptually ('one canonical PaidHandshake inventory feed') without adding format or selection guidance beyond the enum.

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 and resource ('read-only preview of one canonical PaidHandshake inventory feed') and constrains scope to a single feed. It explicitly names the sibling it is NOT (get_published_intelligence_sample), so an agent can disambiguate without opening either schema.

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?

Gives an explicit prerequisite ('Use get_live_inventory first to discover feed inventory') and an explicit exclusion routed to an alternative ('use get_published_intelligence_sample instead for worker-published intelligence products'). Both when-to-use and when-not-to-use are covered.

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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