start_consulting_project_workflow

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

No annotations are provided, so the description carries the behavioral burden. It successfully conveys that this is a governed, multi-stage workflow with approval gates and execution work packets, and that passing a project_id continues an existing project. It does not enumerate every side effect, but it gives materially useful behavioral context beyond the tool name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core statement, followed by one tight usage paragraph, then a compact Args list. There is no filler, and each section serves a distinct purpose for the agent.

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

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

For a workflow tool with 5 parameters, the description covers what it does, when to use it, what each argument means, and the high-level phases it runs through. The output schema covers return details, so that omission is acceptable. It leaves runtime behavior such as async execution slightly implicit, but that is reasonably inferable from the word 'workflow' and the mention of approval gates.

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

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

Schema description coverage is 0%, but the Args section compensates by explaining all five parameters with concrete meaning: objective's purpose, coding_harness's accepted lanes, project_context's contents, project_id's continuation role, and source's host examples. This is far beyond what the schema names alone provide.

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

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

The description opens with a specific verb phrase ('Start or continue') and a concrete resource ('Lightbulb consulting project workflow through Backbone'). It then enumerates the exact request types that belong here, clearly distinguishing this tool from direct coding, GitHub, deployment, connector mutation, and external communication tools.

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

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

The line 'Use this instead of jumping directly to coding, GitHub, deployment, connector mutation, or external communications when...' is an explicit when/when-not statement with named alternative categories. It also describes the qualifying conditions: needs discovery, requirements, scope, SOP impact, approval gates, and execution work packets.

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