Get Program Design

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description goes well beyond this by disclosing enum fallback behavior for `participantAvatarStyle`, omission of the confirmation section when no fields are stored, null versus omitted field handling, and localized defaults. These are behavioral traits an agent cannot infer from the annotations alone, making the description highly transparent.

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 longer than average, but every sentence conveys essential behavior: field inventory, enum values and fallback, null semantics, section omission, and campaign targeting. It is front-loaded with the core action and resource, and code identifiers are used precisely to avoid ambiguity. It loses one point only because the null/default behavior could have been compressed without losing clarity.

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 read-only getter with one optional parameter and an output schema present, the description covers everything needed to invoke it correctly: what fields are returned, enum valid values and default, null behavior, omitted-section behavior, localized defaults, and campaign selection. No critical operational detail is missing.

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% coverage for the single `campaignId` parameter, including its default and how to obtain it from growsurf_create_campaign. The description restates the targeting default but does not add new parameter semantics beyond the schema. Per the rubric, baseline 3 is appropriate when the schema carries the load.

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 and resource: 'Fetch the configured design fields for your GrowSurf program.' It enumerates the exact field groups returned (GrowSurf Window content, colors, sharing sections, avatar styles, Claim Offer Popup, login copy, payout confirmation copy, country labels), which unambiguously distinguishes it from sibling tools like growsurf_get_campaign or growsurf_get_campaign_emails. The inclusion of specific code paths such as `participantAvatarStyle` and `countryLabels` removes any ambiguity about scope.

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 primary use case is implied by the purpose: call this when you need the read-only design configuration of a GrowSurf program. The description does clarify the campaign targeting behavior ('Targets `campaignId` if you pass it, otherwise GROWSURF_CAMPAIGN_ID'), which is useful operational guidance. However, it does not explicitly state when to prefer this over alternatives or when not to use it, leaving the agent to infer routing from the tool name and sibling list.

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