x-tweet-by-conversation

Files (3)

• SKILL.md
• build-conversation-url.py · scripts/
• parse-tweets.py · scripts/

SKILL.md (first lines)

# X — Tweets by Conversation

> Conversation id (root tweet id) → normalized list of every tweet in the thread (focal tweet + replies + sub-replies), with author, engagement, media, cursor.

## Language

All process output to user (progress updates, process notifications) follows the user's language.

## Objective

Given an X conversation id (which equals the root tweet id), collect the focal tweet and every reply / sub-reply visible to the logged-in session, returning structured per-tweet data with pagination cursors.

## Prerequisites

- Active X session in the browser (left sidebar shows logged-in avatar / @handle).
- Network capture is enabled in the browser-act session.

## Pre-execution Checks

### 1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

### 2. Login Verification

If login status for X has been confirmed in the current session → skip this step.

Otherwise: open `https://x.com` and observe the left sidebar:
- User avatar or @handle visible → logged in, continue
- "Sign in" / "Log in" prompt visible → not logged in, inform the user and assist the login flow

User refuses or cannot log in → terminate execution.

## Capability Components

> This Skill's operational boundary = what the user can manually do in their browser. It only reads tweet data already shown to the user, never bypassing authentication. The browser's own JS signs the GraphQL request; the Skill triggers it via URL navigation and reads the response from network traffic. Python scripts under `scripts/` only build URLs and parse responses — they do not call X directly. Run them through the bash tool.

### Network Capture: full conversation thread

Step 1 — build the tweet-detail URL for the conversation root:

`URL=$(python scripts/build-conversation-url.py '{conversation_id}' [--handle {handle}])`

Parameters:
- `conversation_id` (positional): the X conversation id, which equals the root tweet id (the same number you would see in `https://x.com/i/status/<conversation_id>`).
- `--handle`: the root tweet's author handle if known; if unknown, leave the default — `x.com/i/status/<id>` resolves to the same focal tweet because X canonicalises the URL.

Step 2 — navigate and capture the first page:

1. `network requests --clear`
2. `navigate "$URL"`
3. `wait stable --timeout 25000` (timeout is normal on X; proceed)
4. `network requests --type xhr,fetch --filter TweetDetail` → take the latest entry's `request_id`
5. `network request <request_id>` → save full output to a file (e.g. `tmp/x-conversation-page-1.txt`)
6. `python scripts/parse-tweets.py --json-file tmp/x-conversation-page-1.txt --source tweet_detail` → emits JSON `{tweets, count, cursor_top, cursor_bottom}`. The focal tweet is the first element; subsequent elements are replies (in display order). Each reply carries `is_reply: true`, `in_reply_to_id`, `in_reply_to_user`, and `conversation_id == <root tweet id>`, which makes the reply tree reconstructable downstream.

Endpoint characteristic: URL contains `/i/api/graphql/<hash>/TweetDetail`. The query hash rotates; always filter by name.

Step 3 — paginate via scroll to load deeper replies and sub-replies:

1. `network requests --clear`
2. `scroll down --amount 5000`
3. `wait stable --timeout 10000`
4. `network requests --type xhr,fetch --filter TweetDetail` → newest entry's `request_id`
5. `network request <request_id>` → save to `tmp/x-conversation-page-N.txt`
6. `python scripts/parse-tweets.py --json-file tmp/x-conversation-page-N.txt --source tweet_detail`

Repeat Step 3 until any termination condition is met:
- Accumulated unique reply count reaches the user's target.
- `count == 0` on the current page.
- `cursor_bottom` is unchanged across two consecutive pages.
- The page shows a "Show more replies" button gated by visibility filters — `state` reveals it; the Agent may `click <index>` to expand more, then resume scrolling.

Error handling:
- If the focal tweet is deleted or protected, the response carries a `TweetTombstone` entry; `parse-tweets.py` filters tombstones, so the result will be `count: 0` — report to the user and stop.
- If no `TweetDetail` request appears after a scroll, wait 3 s and retry once. Persistent absence after two scrolls means the thread has been fully loaded.
- If a captcha challenge appears (visible in `state` as an authorization prompt), pause and ask the user.

Output example:
```json
{
  "tweets": [
    {
      "type": "tweet",
      "id": "2069990565530214798",
      "url": "https://x.com/Rothmus/status/2069990565530214798",
      "twitter_url": "https://twitter.com/Rothmus/status/2069990565530214798",
      "text": "\"We are going to have a multi-racial nation in Singapore. ...\"",
      "created_at": "Tue Jun 24 23:01:50 +0000 2026",
      "lang": "en",
      "source": "Twitter Web App",
      "retweet_count": 91,
      "reply_count": 84,
      "like_count": 567,
      "quote_count": 12,
      "bookmark_count": 50,
      "view_count": 64140,
      "is_reply": false,
      "is_retweet": false,
      "is_quote": false,
      "quote_id": null,
      "quote_url": null,
      "in_reply_to_id": null,
      "in_reply_to_user": null,
      "in_reply_to_user_id": null,
      "conversation_id": "2069990565530214798",
      "hashtags": [],
      "mentions": [],
      "urls": [],
      "media": [],
      "card": null,
      "place": null,
      "author": {
        "id": "987654321",
        "user_name": "Rothmus",
        "name": "Rothmus",
        "url": "https://x.com/Rothmus",

From browser-act/skills, MIT.

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