Create data source

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true), the description discloses detailed behavioral traits: offline cooking behavior when no URL is given, that live OSC/serial values appear only when a sender/device is present, and the output format (Null CHOP for numeric fields, Null DAT for raw text). 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 a single paragraph containing all necessary information without redundancy, but it is relatively long (123 words). The structure is logical: main purpose, kind-specific details, then output behavior. Could be slightly more concise but remains effective.

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 (10 params, no output schema), the description fully covers the tool's behavior: it explains offline fallback, live data conditions, output format, and binding capability. It leaves no significant gaps for an intelligent agent to infer.

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 provides 100% description coverage for parameters. However, the description adds value by summarizing how parameters relate to each other (e.g., url and kind interaction, fields becoming channels) and explaining the overall output structure beyond individual parameter descriptions.

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 clearly states 'Ingest live external data onto a binding-ready channel/table', specifies the four kinds (json, csv, osc, serial) and contrasts itself as the 'input counterpart' to create_data_visualization and bind_to_channel, distinguishing it from sibling 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 description provides context for when to use each kind (e.g., 'json/csv poll a URL', 'osc listens on a UDP port') and identifies related tools (create_data_visualization, bind_to_channel). However, it does not explicitly state when not to use this tool or offer direct alternatives, leaving some room for inference.

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