Replies to an X product announcement continue arriving after yesterday's questions were answered. You want to find issues worth reading today. Latest-comment retrieval can guide that review, but it is not a guaranteed real-time notification stream.

Keep the observation tied to one post

Confirm the original tweet ID and record the first observation time. A supplementary announcement has a separate discussion source. Preserve identities of comments already seen so repeat appearances do not become apparent growth merely because another batch was retrieved.

Separate newly collected from newly published

Continue with returned cursors and record collection boundaries. A comment first retrieved today may have been published earlier. Visibility, ordering, and previous gaps affect what you encounter. If publication information is available, preserve it separately from your local retrieval time.

Build a follow-up reading queue

Distinguish new problem descriptions, repeated questions, clarified misunderstandings, and irrelevant remarks. Check important claims against the original announcement or supporting material. Do not automatically publish responses. Deliver source-linked items that need reading, verification, or an existing explanation. No new result does not prove the conversation stopped. The workflow allocates attention without promising complete live monitoring or automated support.

Request URL and parameters

GET https://api.trmesh.com/openapi/api/v1/twitter/web/fetch_latest_post_comments

Parameter Type Required Meaning
tweet_id string Yes Tweet ID
cursor string No Cursor

Run the Python example

Install requests and set TRMESH_API_TOKEN in your environment. Replace the sample identifiers with the public object you intend to inspect. Example IDs may no longer be available.

import os
import requests

# Read your own developer key from the server environment.
url = "https://api.trmesh.com/openapi/api/v1/twitter/web/fetch_latest_post_comments"
params = {
    "tweet_id": "1808168603721650364"
}
response = requests.get(
    url, params=params, timeout=30,
    headers={"Authorization": f"Bearer {os.environ['TRMESH_API_TOKEN']}"},
)
response.raise_for_status()
payload = response.json()
print(payload)  # Inspect the actual response before mapping fields

Endpoint documentation · Free profile tool

API calls use your TRMesh account allowance. Check the endpoint price before running a script.