Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add oyorf/personal-workbench-skills --skill douyin-account-datagit clone --depth 1 https://github.com/oyorf/personal-workbench-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oyorf/personal-workbench-skills/douyin-account-data)<a href="https://agentmods.dev/skills/oyorf/personal-workbench-skills/douyin-account-data"><img src="https://agentmods.dev/badge/skills/oyorf/personal-workbench-skills/douyin-account-data/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oyorf/personal-workbench-skills/douyin-account-data"><img src="https://agentmods.dev/badge/skills/oyorf/personal-workbench-skills/douyin-account-data.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00085 | $0.01077 |
| Opus 5 | $0.00043 | $0.00539 |
| Sonnet 5 | $0.00017 | $0.00215 |
| Haiku 4.5 | $0.00009 | $0.00108 |
Grade A, and why
douyin-account-data scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Douyin Account Data
Scope
Only collect data from a Douyin Creator Center account that the user has explicitly authorized. Use Ego Lite on macOS or the bundled Playwright adapter on Windows. Produce data facts for Personal AI Workbench; do not generate content recommendations, account strategy, or publishing actions.
The Windows adapter uses a dedicated local browser profile and the same official-export, validation, and atomic-publish pipeline as macOS. Linux remains unverified; on Linux, explain the limitation and use manually downloaded official Excel files unless the user explicitly asks to test the adapter there. Never claim partial data is complete.
Required inputs
Resolve both paths before collection:
- Personal AI Workbench root containing
Workbench/server/vault-index.mjs. - A private knowledge-base root where
30_self_media/douyin/may be written.
Prefer paths explicitly provided by the user, then PERSONAL_DASHBOARD_ROOT and PERSONAL_DASHBOARD_VAULT_ROOT. If either path remains unknown, ask the user. Never guess a username, home directory, repository name, or Vault name.
Read platform-support.md when setup, Ego Lite, login, Windows, or Linux is involved. Read data-contract.md before changing collection coverage or the Workbench output schema.
Safety gate
Before running:
- Confirm the account belongs to the user or the user is authorized to access it.
- On macOS, confirm Ego Lite is installed and onboarding is complete. On Windows, confirm the Playwright requirements and Chromium browser are installed.
- On macOS, confirm the user has logged into Creator Center inside Ego Lite. On Windows, open the headed Playwright browser and let the user complete first-run QR login or verification there.
- Confirm the target knowledge base is private and is not the public synthetic demo directory in a Git repository.
- Confirm
node, Python, andopenpyxlare available. macOS also requiresjqandego-browser; Windows requires the Pythonplaywrightpackage and an installed Playwright Chromium browser.
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 316 B
- assets/config.example.json 286 B
- references/data-contract.md 1.5 KB
- references/platform-support.md 4.4 KB
- requirements-windows.txt 37 B
- scripts/analyze_snapshot.py 47 KB runs code
- scripts/collect_playwright.py 15 KB runs code
- scripts/collect.sh 7.0 KB runs code
- scripts/ego_collect.sh 17 KB runs code
- scripts/inventory_exports.py 10 KB runs code
- scripts/playwright_collect.py 20 KB runs code
- scripts/publish_workbench_data.mjs 24 KB runs code
- scripts/test_analyze_snapshot.py 3.9 KB runs code
- scripts/test_collect_playwright.py 4.9 KB runs code
- tests/analysis.fixture.json 190 B
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 85 lines · 85 tokens per session scan A f55f31cdf28c
douyin-account-data is a skill published in the GitHub repository oyorf/personal-workbench-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 85 tokens to every session and 1,077 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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