Simple Lab Tools Label Maker

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

Annotations already declare readOnly/not-destructive/idempotent/closed-world, yet the description still adds real behavioral context: no physical print job, no account data stored, overflow is rejected, and the exact return artifacts (printUrl, editUrl, sheet JSON). That is meaningful disclosure beyond the structured hints.

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?

Four dense sentences, purpose front-loaded in the first clause, and every subsequent sentence adds a distinct fact (scope, outputs, error behavior, layout rules). No filler or redundancy.

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?

With 8 parameters, no output schema, and 0% schema description coverage, the description does the necessary work: it explains the return shape and the layout/copy semantics that the schema cannot. The unmentioned enums (template IDs, fonts) are the only notable gap, and those are largely self-describing.

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%, so the description carries the full burden and only partially compensates. It adds genuine semantics for labels (empty strings = blanks), copies (consecutive repetition), and positioning (1-based, row-major), but says nothing about template, fontSize, fontFamily, qrEnabled, or name.

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?

States a specific verb and resource ("Create one printable sheet") plus the additional artifact (editable share link) and the input (plain label text). The function is readily distinguishable from the sibling list_label_templates, but that alternative is never named, so sibling differentiation is implicit rather than explicit.

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?

Gives some operative guidance ("Use empty strings for blank slots", "Does not submit a physical print job") and clarifies the non-persistent scope, but never states when to prefer this over other tools or what preconditions exist. Enough to invoke correctly, not enough to route confidently.

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

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so the safety profile is fully covered. The description adds value by disclosing what each entry contains (dimensions in inches, capacity, placement geometry), but says nothing about ordering, completeness, pagination or error behavior for a list operation.

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?

Two sentences, no filler, and the payoff ('Match the user's label stock') is front-loaded after the content enumeration. Every clause earns its place by either describing the payload or prescribing the timing of the call.

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 zero-param read-only list tool with no output schema, the description supplies the shape of the returned records and the workflow trigger, which is close to sufficient. It stops short of stating whether the list is exhaustive or how templates are identified/keyed, which an agent picking a stock would benefit from knowing.

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 tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly does not invent parameter guidance for a parameterless tool.

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?

States a specific verb (List) and resource (physical label templates) and then enumerates the exact payload an agent gets back -- dimensions, capacity, placement geometry. The phrase 'before creating a sheet' implicitly separates it from the create_label_sheet sibling, so an agent can place it in the workflow without opening the schema.

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?

Gives clear situational context: 'Match the user's label stock before creating a sheet,' which tells the agent this is a precondition/discovery step. It does not explicitly name create_label_sheet as the alternative or state any exclusion, so it stops short of the full when/when-not/alternatives bar.

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