List failed webhook requests in the Dead Letter Queue. These are webhooks that failed after all retry attempts.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of entries to return (default: 20) | |
| status | No | Filter by status (default: all) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of transparency. It explains that the DLQ contains webhooks that failed after all retry attempts, which is useful behavioral context. However, it does not disclose that the status filter allows pending/dead entries, which may slightly conflict with the 'failed' phrasing, and does not mention return format or pagination beyond the schema.
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 two sentences, with the primary action front-loaded and the clarifying definition in the second sentence. Every word earns its place.
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 simple list tool with two optional parameters and an output schema absent, the description is adequate. It clarifies the meaning of the DLQ and the origin of the entries. The only minor gap is the relationship between the status enum and the 'failed' wording, but this is handled by the schema.
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 100%, so the description does not need to explain parameters. It does not add additional meaning beyond the schema, which already documents limit and status defaults and enums.
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 clearly states the tool lists failed webhook requests in the Dead Letter Queue, using the specific verb 'List' and the resource 'Dead Letter Queue'. It further clarifies what these webhooks are (failed after all retry attempts), distinguishing it from sibling tools like nolag_retry_webhook_dlq.
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 clear context for when to use the tool: to inspect webhooks that failed after retries. It does not explicitly exclude alternatives or mention nolag_retry_webhook_dlq for retrying, so it lacks explicit when-not guidance, but the usage is well implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools follow a clear resource-action pattern, but create_actor, create_agent, and create_orchestrator could be confused, as agents and orchestrators are specialized actors. Similarly, publish and dispatch_task both send messages to topics, though descriptions clarify. Overall, boundaries are mostly distinct.
All tools use the nolag_ prefix with consistent verb_noun snake_case naming. Verbs include create, delete, get, list, update, set, retry, dispatch, publish, generate, and configure. No mixed conventions are present.
At 35 tools, this server exceeds the recommended range for a typical MCP server. While each tool serves a purpose, many CRUD operations could be consolidated (e.g., create_actor, create_agent, and create_orchestrator could be one tool with a type parameter). The count feels heavy.
The toolset covers core lifecycle operations for apps, actors, rooms, scopes, and webhooks, plus messaging, task dispatch, blackboard state, and agent event streaming. Minor gaps exist (no explicit agent-specific update, no webhook delete), but agents can work around these with general actor/app operations.
