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get_response_replies

Get nested replies under a single top-level response. Use with list_responses to walk through the discussion thread.

Instructions

Read-only. Nested replies under a single top-level response. Use list_responses first to get response ids, then call this per response to walk the thread.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
response_idYes
limitNo

Implementation Reference

  • Actual implementation of get_response_replies: delegates to list_responses (GraphQL query) since Medium models responses as posts too.
    def get_response_replies(self, response_id: str, *, limit: int = 50) -> list[dict[str, Any]]:
        """Replies under one response. Medium models responses as posts too."""
        return self.list_responses(response_id, limit=limit)
  • Tool registration schema with input_schema requiring response_id and optional limit.
    "get_response_replies": {
        "description": (
            "Read-only. Nested replies under a single top-level response. Use "
            "list_responses first to get response ids, then call this per "
            "response to walk the thread."
        ),
        "input_schema": {
            "type": "object",
            "properties": {
                "response_id": {
                    "type": "string",
                    "description": "Response id from list_responses.",
                },
                "limit": {
                    "type": "integer",
                    "default": 50,
                    "description": "Max replies to return. Default 50.",
                },
            },
            "required": ["response_id"],
        },
    },
  • Dispatch handler in _dispatch() that calls the client's get_response_replies method.
    if name == "get_response_replies":
        return c.get_response_replies(args["response_id"], limit=args.get("limit", 50))
  • Helper method walk_responses() that uses get_response_replies to walk one level of replies under each top-level response.
    def walk_responses(
        self,
        post_id: str,
        *,
        skip_user_id: str | None = None,
    ) -> Iterator[dict[str, Any]]:
        """Yield every top-level response + one level of replies."""
        for r in self.list_responses(post_id):
            if skip_user_id and (r.get("creator") or {}).get("id") == skip_user_id:
                continue
            yield {"depth": 0, "parent_id": None, **r}
            rid = r.get("id")
            if rid and (r.get("postResponses") or {}).get("count"):
                for child in self.get_response_replies(rid):
                    if skip_user_id and (child.get("creator") or {}).get("id") == skip_user_id:
                        continue
                    yield {"depth": 1, "parent_id": rid, **child}
Behavior3/5

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

The description declares read-only but lacks details on pagination, error handling, or rate limits. With no annotations, the description could disclose more behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with 'Read-only.' Every sentence adds value; no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite missing parameter semantics, the description provides sufficient workflow context for the tool's low complexity, though behavioral details are lacking.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description does not explain the parameters (response_id and limit) beyond referencing response IDs from list_responses. No added meaning over schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves nested replies under a single top-level response and distinguishes from list_responses by indicating the workflow.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to use list_responses first to get response IDs, then call this tool per response to walk the thread, providing clear when-to-use guidance.

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

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