Create datamosh / time-smear effect

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

Annotations indicate the tool is not read-only and not destructive. The description adds important behavioral context: it creates nodes, returns a container with output, and notes fallback behavior for 'time_echo' mode. No contradictions with annotations.

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 three sentences long, each serving a clear purpose: stating the tool's function, detailing modes and parameters, and describing the output. No wasted words; 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?

Given the complexity (7 parameters, 3 modes, no output schema), the description covers all major behaviors, return value, and parameter interactions. It could briefly mention the container's internal structure, but overall it's complete enough for an agent to use the tool correctly.

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 covers all parameters (100%). The description enhances understanding by explaining the algorithmic differences between modes, the effect of decay and displace, and the fallback for time_echo. This adds meaning beyond the schema definitions.

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 specifies a concrete action: building a datamosh effect network in one call, with clear verb+resource. It lists three distinct modes, distinguishing it from sibling tools like create_glitch or create_feedback_network by focusing on time-smear and ghost-trail effects. The purpose is unmistakable.

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 provides explicit guidance on how to use each mode, including the behavior of key parameters. However, it does not explicitly state when to avoid this tool in favor of siblings, but given the specific use case, the guidance is sufficient.

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