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LocationLists

by io.github.kylehawke-stack
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Send feedback

send_feedback

Send a message to the LocationLists team: wrong or missing data in a dataset, something that did not work, a pricing question, an idea, or anything else. Ask the user before sending and use their words. Ask for their email so the team can reply, and pass it only if they gave it; never guess or invent one. Called with neither email nor email_declined, it sends nothing and asks for the email. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailNoThe user's email, only if they gave it
datasetNoDataset slug it concerns, if any, e.g. generac-dealers
messageYesThe feedback, in the user's words (5-4000 characters)
categoryNoWhat it is about (default other)
email_declinedNoTrue only when you asked the user for their email and they chose not to leave one

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / email / description
      Previous value: -"The user's email, only if they chose to leave it"New value: +"The user's email, only if they gave it"
    • addedInput schema / properties / email_declined
      Added value: +{
+  "description": "True only when you asked the user for their email and they chose not to leave one",
+  "type": "boolean"
+}
  2. Added

TDQS

A4.6/5.0
Behavior5/5

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

With annotations all false and therefore uninformative, the description carries the full burden and does excellent work: it discloses the consent requirement, the handling of the user's email, the rule never to guess or invent an email, and the fallback behavior when neither email nor email_declined is provided. This goes well beyond a generic 'sends feedback' statement.

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?

The description is compact, front-loaded with purpose, and every sentence earns its place. It packs consent, parameter behavior, and a fallback rule into a short paragraph without padding.

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?

For a simple one-required-parameter feedback tool with no output schema or nesting, the description covers the important agent-facing behaviors: message source, email consent, email_declined, and what happens when neither email field is set. It could arguably add what the user sees after sending, but that is minor here.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful semantics beyond the schema: the email must only be passed if the user gave it, email_declined must be set only after asking, and calling with neither sends nothing. This clarifies parameter interplay rather than repeating schema text.

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?

The description names a specific verb and resource: 'Send a message to the LocationLists team.' It lists concrete use cases (wrong/missing data, something did not work, pricing question, idea) and is clearly distinct from sibling tools like get_dataset or buy_dataset.

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?

It communicates when to use the tool by enumerating feedback categories ('wrong or missing data... pricing question... anything else'), and gives operational guidance such as asking the user before sending and using their words. It does not explicitly name alternatives or exclusions, but sibling context makes the appropriate use clear.

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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