stream_get_repliesFetch the reply messages in a thread, given the parent message id. GET /api/v2/chat/messages/{parent_id}/replies.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max replies (<=300). Default 25. | |
| parent_id | Yes | Parent (thread-root) message id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals a safe read operation, and the description's GET/fetch language is consistent with it. The description adds the endpoint but does not disclose response shape, pagination behavior, or edge cases; for a simple read-only tool this is adequate but not rich.
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 compact sentences: the first states the purpose and key input, and the second provides the endpoint. There is no filler, redundancy, or unnecessary detail.
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 low-complexity read-only fetch, the schema covers both parameters, annotations cover safety, and the description states the resource and endpoint. It leaves response format and pagination implicit, but these are not essential for correctly selecting and invoking the tool.
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%, with both parent_id and limit already documented, including limit's default and maximum. The description only restates parent_id and adds no semantic information beyond what the schema provides.
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 uses a specific verb+resource ('Fetch the reply messages in a thread') and identifies the required key ('parent message id'). The endpoint makes the target resource unambiguous and distinguishes it from siblings like stream_get_message, stream_get_reactions, and stream_query_threads.
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 clearly indicates the context for use: given a parent message id, fetch its thread replies. However, it does not explicitly state when not to use this tool or name alternatives, so usage guidance is mostly implied by the name and sibling set.
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 targets a distinct resource and action: app info, channel state, messages, reactions, replies, unread counts, and various query types. Even similar tools like get_channel vs query_channels are clearly separated by single-item vs list operations.
All tools follow the consistent pattern stream_<verb>_<resource> (e.g., stream_get_message, stream_query_channels, stream_send_message). Verb usage is coherent across the set.
With 13 tools, the set is well-scoped for a chat API server, covering core read, query, search, and write operations without excessive fragmentation.
Core chat workflows are covered: app info, channel access, messaging, reactions, threads, unread counts, and user/channel queries. Missing mutations like channel/message update or delete are notable but not severe, as the get-or-create channel behavior and send actions cover primary use cases.