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This was a duplicate manual listing. Use Summer’s official listing, imported from the official MCP Registry. Summer’s MCP server remains active at https://api.gosummer.ai/mcp. Setup and documentation: https://gosummer.ai/docs/mcp-clients.

Read the existing AI employee choices and four explained company questions, five optional policy preferences, current answers, connected channel/teammate/patient-portal choices, exact preview and agent setup instructions

summer_onboarding_policies_read
Read-onlyIdempotent

Read the existing AI employee choices and four explained company questions, five optional policy preferences, current answers, connected channel/teammate/patient-portal choices, exact preview and agent setup instructions. Company branding is already known. No long questionnaire is returned.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "company": "<company>"
    },
    "name": "summer_onboarding_policies_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
companyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.4/5.0
Behavior3/5

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 useful scoping context ('Company branding is already known. No long questionnaire is returned.'), but says nothing about auth requirements, pagination, or the shape of the returned state beyond these negatives.

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

Conciseness2/5

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

The bulk is a single run-on enumeration that restates the title verbatim, with the meaningful 'no long questionnaire' note buried at the end instead of front-loaded. The detail-to-signal ratio is poor for a one-parameter read tool.

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?

No output schema exists and annotations only cover safety, so the description carries responsibility for explaining return contents and the required company identifier. It gives a loose list of returned items but no structure and omits the parameter entirely.

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

Parameters2/5

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

Schema description coverage is 0% and there is one required 'company' parameter with a UUID format. The description never mentions this parameter, leaving the agent to infer the UUID requirement entirely from the raw schema pattern.

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

Purpose3/5

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

The description enumerates the resources returned (AI employee choices, company questions, policy preferences, answers, channel/teammate/portal choices), so the agent can infer this reads onboarding policy state. However, it lacks a crisp verb+resource summary sentence and never distinguishes itself from the closely named siblings summer_onboarding_policies_save, summer_onboarding_policies_publish, or summer_onboarding_readiness.

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

Usage Guidelines2/5

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

There is no statement of when to call this versus the save/publish/readiness siblings, no prerequisite context, and no exclusions. The 'read' suffix is the only signal, which the structured name already provides.

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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