ai-business-system-advisor-mcp

by tenkai2018

Overview Schema Source Related Servers Discussions Admin

Export Intake Packet

export_intake_packet

Read-onlyIdempotent

Creates a structured intake packet combining business context, findings, risks, and workflow recommendations into a shareable markdown and JSON document.

Instructions

Creates a structured public-safe markdown and JSON intake packet with business context, findings, risks, recommended workflow, missing information, and confidence.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "export_intake_packet"
  }
}

Input Schema

Name	Required	Description
`notes`	No	Any additional context the user wants considered in the review.
`offer`	No	Core product, service, package, or outcome the business sells.
`aiIdea`	No	AI or automation idea the user is considering.
`teamSize`	No	Approximate team size and key roles involved in the workflow.
`userNotes`	No	Additional notes the user wants included in the intake packet.
`goal90Days`	No	Desired business or workflow outcome over the next 90 days.
`constraints`	No	Known constraints such as budget, team capacity, tools, timeline, compliance needs, or data access.
`currentGoal`	No	Current business goal the user wants the review to support.
`riskSummary`	No	Structured trust and control risk findings from a prior tool result.
`businessType`	No	Type of business, such as ecommerce, SaaS, consulting, agency, local service, or solo business.
`revenueModel`	No	How the business earns revenue, such as projects, retainers, subscriptions, services, or products.
`riskConcerns`	No	Concerns related to customer trust, brand reputation, legal exposure, sensitive data, or quality control.
`touchpointMap`	No	Structured customer touchpoint map from a prior tool result.
`currentProblem`	No	Main business or workflow problem the user wants to solve.
`targetCustomer`	No	Primary customer segment or buyer the business serves.
`businessContext`	No	Structured business context from a prior tool result or user notes.
`currentWorkflow`	No	How the relevant workflow currently works, including manual steps, tools, handoffs, and review points.
`bottleneckSummary`	No	Structured bottleneck findings from a prior tool result.
`preferredNextStep`	No	Preferred next-step category or support style to include in the packet.
`opportunitySummary`	No	Structured AI opportunity findings from a prior tool result.
`recommendedNextStep`	No	Structured next-step recommendation from a prior tool result.
`recommendedWorkflow`	No	Structured first workflow recommendation from a prior tool result.

Output Schema

Name	Required	Description
`confidence`	Yes	Confidence level based on the clarity and completeness of the provided business context.
`packetJson`	Yes	Structured intake packet data for handoff or deeper review.
`packetMarkdown`	Yes	Public-safe intake packet formatted as markdown.
`missingInformation`	Yes	Information the user should provide before deeper review or implementation.
`recommendedPrivateReview`	Yes	Public-safe recommendation for the next deeper review category.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.10Jul 30, 2026

TDQS

B3.4/5.0

Behavior3/5

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

Annotations already indicate readOnly, idempotent, non-destructive behavior. The description adds 'public-safe' and lists output components, but does not disclose that the tool depends on prior structured inputs from other tools. This gap in behavioral context limits the score.

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?

The description is a single sentence that efficiently lists key packet components. It is front-loaded with the main action. However, it could benefit from slight restructuring to improve readability.

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

Completeness3/5

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

While the description summarizes the output, it does not explain how to use the 22 optional parameters or that they likely come from prior tool outputs. Given the complexity and the presence of an output schema, more contextual guidance would improve completeness.

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% with each parameter described. The description does not add additional meaning or usage details beyond the schema, so it meets the baseline of 3 without exceeding it.

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 clearly states the tool creates a structured intake packet with specific content. It uses a specific verb ('Creates') and resource ('intake packet'), and lists key components. It distinguishes itself from sibling analysis tools by being an export/creation tool rather than an analytical one.

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?

No guidance is provided on when to use this tool versus its siblings. Given 9 sibling tools, explicit usage context or prerequisites (e.g., requiring prior output from analysis tools) would be helpful but is absent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server