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Validate Agent Office Plan Graph

validate_agent_office_plan_graph
Read-onlyIdempotent

[read] Checks a plan graph without saving it: the graph as it would be saved (references of other merchants dropped), its errors (empty = it can be saved) and each node's required missing_needs still to be given at run start.

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": {
      "agent_office_plan_nodes": "<agent_office_plan_nodes>"
    },
    "name": "validate_agent_office_plan_graph"
  }
}

Input Schema

NameRequiredDescriptionDefault
agent_office_plan_edgesNo
agent_office_plan_nodesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already state readOnly, idempotent, and non-destructive behavior. The description adds meaningful behavioral detail beyond annotations: it does not save, returns the graph as it would be saved, drops references to other merchants, reports `errors`, and exposes each node's required `missing_needs`.

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 a single front-loaded sentence with no filler. The `[read]` marker, validation behavior, and return details are all packed efficiently without redundant text.

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?

There is no output schema, and the description usefully explains key return concepts such as `errors` and `missing_needs`. However, with zero schema parameter descriptions, it leaves input semantics under-specified for an agent that must construct the nodes/edges payload.

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%, so the description must explain the two parameters. It does not clarify `agent_office_plan_nodes` versus `agent_office_plan_edges`, nor does it mention the optional/null nature of edges. Only an indirect reference to 'each node' hints at the node parameter.

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 uses a specific verb and resource: it 'Checks a plan graph without saving it.' The phrase 'without saving it' directly distinguishes this validation tool from sibling create/edit tools such as create_agent_office_plan_graph and edit_agent_office_plan_graph.

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?

The description clearly implies when to use the tool: validating a graph before saving, with `errors` empty meaning it can be saved. It does not explicitly name the alternative save/create tool, but the usage context is 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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