Dokploy MCP Server

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

Annotations provide key behavioral hints: readOnlyHint=false (mutation), destructiveHint=false (non-destructive), idempotentHint=true (safe to retry), and openWorldHint=true (flexible inputs). The description adds no behavioral context beyond this, such as what 'update' entails (e.g., partial vs. full updates), side effects, or error conditions. Since annotations cover the core safety profile, the description meets the lower bar but doesn't enhance understanding of the tool's behavior in practice.

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 concise and structured as a parameter list, which is efficient for a tool with many inputs. However, it lacks a clear introductory sentence stating the tool's purpose, making it slightly less front-loaded than ideal. The formatting with bullet points is helpful, but the content is under-specified rather than overly verbose, keeping it relatively tight.

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 (13 parameters, 0% schema coverage, no output schema) and the mutation nature (readOnlyHint=false), the description is inadequate. It doesn't explain what the tool returns, how updates affect existing configurations, or the relationships between parameters (e.g., if 'endpoint' is required when certain booleans are true). With rich annotations but no output schema and poor parameter documentation, the description leaves significant gaps for an agent to understand the tool's full context.

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 description coverage is 0%, so the description must compensate by explaining parameters. It only lists parameter names and types without any semantic meaning (e.g., what 'appBuildError' controls or how 'endpoint' is used). This adds minimal value beyond the schema, failing to clarify the purpose of the 13 parameters, especially the many boolean flags that likely toggle notification events. With low coverage, a higher score requires meaningful explanations, which are absent here.

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 is essentially a tautology that restates the tool name ('notification.updateCustom') with minimal additional context. It mentions 'POST' and lists parameters but doesn't clearly state what the tool actually does (e.g., updating custom notification settings for specific events). While it implies updating something related to notifications, it lacks a specific verb+resource combination that distinguishes its purpose from sibling tools like other notification update 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?

There is no guidance on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an existing custom notification), context for updates (e.g., modifying event triggers or endpoints), or comparisons with other notification tools (e.g., dokploy_notification_updateDiscord). Without this, an agent must infer usage from the parameter list alone, which is insufficient for clear decision-making.

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