get_template

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

No annotations present, so description fully carries the burden. Discloses that output is litegraph format (not API), token reduction stats, and that online templates require node/model verification.

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?

Well-structured with front-loaded purpose, then clear bullet-like explanation of parameters and usage context. Every sentence adds value.

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 tool's complexity (4 parameters, output schema exists, sibling tools like search_templates and run_template), the description is complete. It explains the output format, prerequisites, and next steps.

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 coverage is 0%, but description explains all four parameters in detail: name, source (behavior of online vs installed), pack (required for installed), and fmt (flowzip vs json, with token savings). Adds significant meaning beyond schema.

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?

Clearly states the verb 'Fetch', resource 'workflow template', and distinguishes between online and installed sources. Does not explicitly differentiate from sibling 'search_templates' but provides enough context to avoid confusion.

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?

Provides explicit guidance on when to use online vs installed, flowzip vs json, and mentions post-fetch steps like adapting to API format or checking nodes/models via other tools.

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