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solver_plan_domain_intelligence

Destructive

Plan domain intelligence by invoking the solver agent to analyze objectives and structured inputs.

Instructions

Run the solver domain agent action plan_domain_intelligence.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior3/5

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

The description adds some context beyond the annotations by noting that the call routes through the domain-agent dispatcher and runs under JWT, tenant, and company scope. It does not address the side-effect profile implied by destructiveHint=true and readOnlyHint=false, but it does not contradict the annotations either.

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 compact, front-loads the action name, and uses a clean Args section. Every sentence adds some context (domain, routing, parameters), though the content is thin.

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?

For a 2-parameter tool with an output schema, some brevity is acceptable, but this description lacks a functional definition of `plan_domain_intelligence` and gives no guidance on what to put in `message` or `inputs`. The large family of sibling domain-planning tools makes this gap more serious.

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?

With 0% schema description coverage, the description must supply parameter meaning, and it does provide one-line semantics: message is a 'free-text objective' and inputs is an 'Optional JSON string of structured inputs.' However, it does not specify the expected JSON structure or any constraints for the objective, leaving the parameters under-specified.

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 states a specific verb ('Run') and resource (the solver domain agent action `plan_domain_intelligence`), and the 'solver' qualifier helps distinguish it from sibling *_plan_domain_intelligence tools. However, it never explains what planning domain intelligence actually accomplishes, so the purpose remains vague beyond invoking a named action.

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 given about when to choose this tool over the many sibling tools, including other *_plan_domain_intelligence variants or the generic `dispatch_domain_agent`. The routing note ('Routes through the platform's domain-agent dispatcher') describes mechanics, not usage conditions or exclusions.

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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