Intended Audience

This page describes who the dokobot-intel-toolkit API is built for, what background you are expected to bring, and how the different parts of the toolkit map to your day-to-day workflows. Understanding the intended audience helps you decide which components you need, which are optional, and how deeply you need to read before making your first API call.

Primary audience

The dokobot-intel-toolkit API is designed for intermediate-level developers who want to automate the daily work of monitoring AI and tech communities across multiple platforms and turning that raw signal into actionable, monetizable content ideas — particularly for Xiaohongshu (Little Red Book).

You are the right audience if you:

• Write Python and can read PowerShell scripts without hand-holding.
• Are comfortable operating a CLI and managing a local environment (Python ≥ 3.11, Node.js ≥ 22, Windows with PowerShell).
• Have existing login sessions on platforms such as X (Twitter), Reddit, V2EX, or Bilibili that you want the scraping pipeline to reuse.
• Are building or maintaining a content-production workflow and want structured intelligence reports delivered daily rather than assembled by hand.

This is not a beginner-friendly graphical tool. The API surfaces its capabilities through CLI scripts, a browser bridge extension, and optionally through WorkBuddy Skills — all of which require you to configure your own environment.

What you are expected to know

How the toolkit maps to your role

If you consume the full scraping pipeline

Your primary workflow is: check bridge readiness → scrape platforms → parse and clean raw data → compare against yesterday's baseline → generate the daily intelligence report. You interact with dokobot_ready.py to confirm the dokobot Edge bridge is active, then invoke the PowerShell scraping scripts and Python parse, clean, comparison, and report scripts in sequence. The output is a structured report that surfaces monetization signals for content repurposing.

If you use only specific WorkBuddy Skills

The three Skills — bili-subtitle, deck-studio, and xhs-commercial-growth — are self-contained and can be enabled independently of the scraping pipeline. You install them by placing the skill package in ~/.workbuddy/skills/ and activating them inside the WorkBuddy application. You do not need the dokobot Edge bridge or the PowerShell scraping scripts to use a Skill on its own.

If you are integrating the toolkit into a larger pipeline

You are likely calling the CLI scripts programmatically — for example, invoking dokobot_ready.py to gate a scheduled job, or chaining the incremental comparison scripts against a stored baseline to feed a downstream notification system. In this case, understanding the device ID output (DEVICE_ID:<uuid> vs NO_DEVICE) and the file conventions used by the parse and clean scripts is the most important thing to get right before you automate.

Who this toolkit is NOT designed for

• Non-developers who need a GUI or a hosted service — all interaction is through scripts and the CLI.
• macOS or Linux users — the PowerShell scraping scripts require Windows. The Python and Skill components may run cross-platform, but the authenticated scraping layer does not.
• Anonymous scrapers — the toolkit is built around reusing your own existing browser login sessions via the dokobot Edge bridge. It does not store or manage credentials, and it will not work without an active, authenticated Edge session on platforms that require login.
• High-volume or production data pipelines — the serial, rate-limit-aware scraping design is intentional and optimized for a single operator's daily cadence, not for concurrent or high-frequency data collection.

Confirming the toolkit is set up for your environment

Before invoking any scraping script, verify that the dokobot Edge bridge is active and that your environment meets the expected prerequisites. The following check tells you immediately whether authenticated scraping can proceed.

# Run from the repository root in PowerShell
python scripts/dokobot_ready.py

Expected output when the bridge is active and you are the right operator:

DEVICE_ID:3f7a1c2e-84b0-4d9e-a512-0e6f3d8c1b77

This confirms that the dokobot Edge bridge extension is running in Microsoft Edge, that your login sessions are available to the scraping scripts, and that you are ready to proceed with the rest of the pipeline.

Expected output when the bridge is not active:

NO_DEVICE

If you see NO_DEVICE, open Microsoft Edge and activate the dokobot bridge extension before continuing. This output means none of the authenticated scraping scripts will be able to reach login-walled platforms such as X or Reddit.

Verifying a WorkBuddy Skill is available (bili-subtitle example)

If you are using only the WorkBuddy Skills and do not need the scraping pipeline, confirm the skill package is installed in the correct location.

# Check that the bili-subtitle Skill is present in the WorkBuddy skills directory
ls ~/.workbuddy/skills/bili-subtitle

Expected output (directory exists and is populated):

skill.yaml   README.md   ...

Once the directory is present, open the WorkBuddy application and enable the skill from within the app. Skills are stored with disable: true by default and must be explicitly activated.

• dokobot Edge bridge — Understand how the browser bridge extension works and why it is required for authenticated scraping on login-walled platforms before running any scraping script.
• Authenticated scraping — Learn what login-state scraping means in this context, which platforms require it, and how the dokobot CLI relays requests through your existing Edge session.
• Monetization signal — Understand what the pipeline classifies as a monetization signal and how signals are ranked and surfaced in the daily intelligence report.
• Incremental comparison — Learn how the baseline diff step works and why comparing today's data against yesterday's snapshot is central to the daily workflow.
• WorkBuddy Skill — Understand the Skill packaging model, how to install and enable a Skill, and when to use the bili-subtitle, deck-studio, or xhs-commercial-growth Skills independently of the scraping pipeline.
• device ID — Learn what the DEVICE_ID:<uuid> output from dokobot_ready.py means and how it gates the rest of the pipeline.