compareVersions
Compare two versions of content in Adobe Experience Manager to identify differences and track changes.
Instructions
Compare two versions of content
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| version1 | Yes | ||
| version2 | Yes |
Compare two versions of content in Adobe Experience Manager to identify differences and track changes.
Compare two versions of content
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | ||
| version1 | Yes | ||
| version2 | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic function ('compare') without detailing what the comparison entails (e.g., returns differences, metadata, or a visual output), whether it's read-only or has side effects, or any constraints like rate limits or authentication needs. This leaves critical behavioral traits unspecified, making it inadequate for safe and effective use.
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, concise sentence ('Compare two versions of content') that is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, making it efficient and easy to parse for an agent.
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 of a comparison tool with 3 parameters, no annotations, no output schema, and low schema coverage, the description is incomplete. It fails to explain the comparison output, parameter semantics, behavioral traits, or usage context. While conciseness is good, the description lacks the necessary details to compensate for the missing structured data, leaving gaps in understanding.
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 has 3 parameters with 0% description coverage, so the schema provides no semantic information. The description does not explain what 'path', 'version1', or 'version2' represent (e.g., file paths, version IDs, timestamps), their formats, or how they relate to the content being compared. This lack of parameter meaning beyond the schema's basic types significantly hinders correct invocation.
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 'Compare two versions of content' clearly states the action (compare) and target (versions of content), avoiding tautology with the tool name. However, it lacks specificity about what 'content' refers to (e.g., pages, assets, components) and how the comparison is performed (e.g., diff, side-by-side view), making it somewhat vague. It does not distinguish this tool from potential siblings like 'getVersionHistory' or 'restoreVersion', which reduces its clarity.
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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., needing existing versions), exclusions (e.g., not for comparing non-versioned content), or related tools like 'getVersionHistory' for listing versions first. Without such context, an agent must infer usage from the tool name alone, which is insufficient for optimal selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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