comfy_agentic_assist

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

With no annotations present, the description carries the full burden of behavioral disclosure and does so thoroughly. It explains the internal campaign steps, the optional vision-check, the maximum retry count of 3, the MCP sampling requirement, the fallback behavior, and the exact return format. This gives the agent a strong mental model of what will happen when invoked.

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 efficiently structured: a one-line purpose statement, a compact bullet-like process summary, a prerequisite and fallback note, and a clearly labeled return format and example. Every section earns its place, and the most important information is front-loaded.

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 single-parameter tool with an output schema, the description is remarkably complete. It covers what the tool does, the steps it performs, constraints (MCP sampling, max 3 retries), fallback behavior, return format, and a usage example. An agent has sufficient information to decide when to call it and what to pass.

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?

The input schema already documents the single 'goal' parameter at 100% coverage, so the baseline is 3. The description adds value by including a concrete example ('Create a cinematic aerial shot of a cyberpunk city') that demonstrates the expected natural-language input style and by framing the parameter as a 'creative goal' within the agentic workflow.

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, 'Multi-step agentic generation via MCP sampling,' and then details the full workflow: planning, workflow selection, generation, optional vision-checking, and retries. This clearly distinguishes it from sibling tools like comfy_generate or comfy_workflows by emphasizing the agentic, multi-step campaign nature.

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 description gives clear context: this tool is for multi-step agentic generation campaigns and requires a host with MCP sampling. It also mentions a fallback to a manual tool sequence when sampling is unavailable, which helps an agent understand when the tool can run. However, it does not explicitly name alternatives or state 'use this instead of comfy_generate for complex goals,' leaving some inference to the agent.

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