get_list_statusCheck the processing status of a lead list.
Use this to POLL after calling generate_batch. Call every 15-30 seconds until processing_status is 'completed' or 'failed'. When completed, call export_list. When failed, submit a new batch.
| Name | Required | Description | Default |
|---|---|---|---|
| list_id | Yes | List UUID from generate_batch or generate_sequence response. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, idempotentHint), the description discloses polling behavior, the expected check cadence, and the status values that indicate completion or failure. This adds operational context not present in the schema or annotations.
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 front-loaded with the core purpose, followed by terse, actionable instructions. Each sentence serves a distinct function with no redundancy, fitting within three lines.
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?
The tool has a single parameter, an output schema, and thorough annotations. The description covers the operational workflow (poll, terminal states, next actions) comprehensively, so nothing essential 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 complete coverage (100%) for list_id, describing it as the UUID from generate_batch or generate_sequence response. The description does not add new parameter semantics but indirectly reinforces the source of the ID, so the baseline 3 is appropriate.
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 'Check the processing status of a lead list,' using a specific verb and resource. It distinguishes this tool from siblings like generate_batch, export_list, list_lists, and list_campaigns by focusing on status polling for a generated list.
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?
It provides explicit instructions to use this tool after calling generate_batch, with a polling interval of 15-30 seconds. It also specifies terminal conditions and next actions, making it clear when to use this vs alternatives.
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.
Each tool has a distinct purpose: list_campaigns provides campaign IDs, generate_batch and generate_sequence handle async batch and sync single generation respectively, get_list_status polls progress, export_list retrieves completed results, and list_lists browses past batches. The descriptions clearly differentiate the overlapping generate tools with explicit usage guidance.
All tool names follow a consistent verb_noun pattern with snake_case (e.g., list_campaigns, generate_batch, export_list). The verbs are clear and the nouns accurately reflect the resources/actions, making the API predictable.
With 6 tools, the server is well-scoped for its purpose of generating and managing email sequences. Each tool serves a necessary role in the workflow, and the count is ideal—not overwhelming, not sparse.
The tool set covers the full lifecycle: discover campaigns, submit batch or single-lead generation, poll status, retrieve results, and browse past batches. There are no obvious missing operations that would prevent an agent from completing the core workflow.