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coding_run_tests

Destructive

Triggers the Lightbulb coding domain agent to run tests under your JWT, tenant, and company scope. Provide a free-text objective and optional structured JSON inputs.

Instructions

Run the coding domain agent action run_tests.

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

B3.2/5.0
Behavior3/5

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

The annotations already carry readOnlyHint=false, destructiveHint=true, and openWorldHint=true; the description does not contradict them. It adds that the call is scoped to the caller's JWT/tenant/company and routes through the domain-agent dispatcher, which is useful auth/routing context, but it says nothing about side effects or what happens when tests run.

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-loaded with the action, and the Args list is scannable. The routing sentence adds useful scope context without padding.

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?

For a two-parameter optional-input wrapper with an output schema, the description is close to adequate, and return-value details are not required. However, it omits what the run_tests action actually does, when to reach for it versus sibling coding tools, and what kind of message/inputs are expected, so an agent can invoke it but may not reliably know if it is the right tool.

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?

The schema only provides types and defaults, so the Args block is the main semantic source. 'message: Free-text objective' and 'inputs: Optional JSON string of structured inputs' add meaning beyond the schema, but they are vague and don't specify expected input keys or formatting for run_tests.

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

Purpose4/5

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

The first sentence names a specific verb and resource ('Run ... action run_tests') and the routing note clarifies this is a domain-agent dispatcher call, distinguishing it from direct coding tools. It is clear enough that an agent knows it invokes the run_tests action, though it doesn't say what running tests entails.

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 when-to-use guidance, exclusions, or alternatives are given. The description never mentions how to choose this over coding_run_command, coding_run_pipeline, or other coding_* tools, so an agent must infer selection from the name alone.

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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