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start_consulting_project_workflow

Initiate a structured consulting project workflow for business outcomes, custom agents, or process changes, ensuring discovery, requirements, and approval gates before execution.

Instructions

Start or continue the Lightbulb consulting project workflow through Backbone.

Use this instead of jumping directly to coding, GitHub, deployment, connector mutation, or external communications when a user has a project idea, custom agent request, workflow automation request, SOP/process change, modernization request, or build request that still needs discovery, requirements, scope, SOP impact or referenced SOPs, approval gates, and execution work packets.

Args: objective: The project idea or business outcome the user wants to achieve. project_context: Optional JSON object with known facts, current systems, requirements, constraints, uploaded-doc references, or host context. project_id: Optional existing Lightbulb project identifier to continue. source: Host/source string such as codex, claude_code, chatgpt, cursor, or mcp.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectiveYes
project_contextNo{}
project_idNo
sourceNomcp

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. However, it only explains the tool's purpose and input parameters, without mentioning side effects, destructive actions, authentication needs, or internal process behavior. The mention of 'through Backbone' is vague.

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 well-structured with a clear opening sentence and an 'Args' section. It is succinct but could be slightly tightened by reducing redundant phrases in the use-case list. However, it remains easy to read and front-loaded.

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?

The description lacks information about the tool's output or return values, and does not mention prerequisites, failure modes, or the workflow lifecycle. While input parameters are well-described, the overall context is incomplete for a workflow tool that likely produces side effects.

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

Parameters4/5

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

Although schema description coverage is 0%, the 'Args' section in the description provides detailed explanations for each parameter: objective, project_context, project_id, and source. This adds significant meaning beyond the raw schema, clearly describing what each parameter represents.

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 'Start or continue the Lightbulb consulting project workflow through Backbone.' It provides a specific verb and resource, and distinguishes from siblings by listing alternative actions (coding, GitHub, deployment) and specifying use cases like project ideas and build requests.

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

Usage Guidelines5/5

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

Explicit when-to-use and when-not-to-use guidance is provided. The description states to use this tool for project ideas, custom agent requests, etc., and to avoid jumping directly to coding, GitHub, or deployment. This clearly differentiates from sibling tools.

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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