Retrieve comments for a specific Substack post by providing its post ID. Returns commenter name, comment body, date, and reaction counts to analyze audience engagement.
Get comments on a published post. Returns commenter name, comment body, date, and reaction counts.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max comments to return (default 20) | |
| post_id | Yes | The post ID to get comments for |
Changes observed during successful MCP inspections.
Input schema / properties / limit / maximumAdded value: +100Input schema / properties / limit / minimumAdded value: +1Input schema / properties / limit / typePrevious value: -"number"New value: +"integer"Input schema / properties / post_id / exclusiveMinimumAdded value: +0Input schema / properties / post_id / maximumAdded value: +9007199254740991Input schema / properties / post_id / typePrevious value: -"number"New value: +"integer"v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers the safety profile, and the description mentions returned data rather than side effects. However, it does not disclose behaviors such as pagination, ordering, or possible empty results, so transparency is adequate but not detailed.
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 compact and information-dense, with exactly two sentences and no redundant phrasing. Every word contributes to understanding the tool's purpose or output.
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 read operation, the description sufficiently identifies the required post_id and the returned fields. The absence of an output schema is partially mitigated by listing expected fields, though details like sorting or pagination behavior are not mentioned.
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 fully documents both parameters, including constraints, defaults, and descriptions. The tool description adds no additional semantic nuance beyond what the schema already provides, so this dimension is at baseline.
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?
Clearly states the action ('Get'), the resource ('comments on a published post'), and the returned fields. The qualifier 'published' helps distinguish from draft-related sibling tools, making the purpose immediately identifiable.
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?
Provides no explicit guidance on when to use this tool versus alternatives, no named sibling tools, and no conditions or exclusions. The only contextual hint is 'published post', which is implicit rather than actionable guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.