OpenBiliClaw
本地私有、开源的自进化跨平台 AI 内容发现 Agent：先理解你，再主动从 B站、小红书、抖音、YouTube、X、知乎、Reddit、微博等平台与开放 Web 寻找内容。（支持 deepseek harness 插件） | Local-first open-source cross-platform AI content discovery agent: understands you, then proactively finds content across Bilibili, Xiaohongshu, Douyin, YouTube, X, Zhihu, Reddit, Weibo and the open web.（support deepseek harness plugin）
Runs with mockssource: GitHubhomepagePythonMITcommit 3c53294e7679
Python, MIT licensed. The project labels itself: ai agent, bilibili, chrome extension, content discovery, cross platform, deepseek harness, douyin and dsh.
OpenBiliClaw runs, with stand-ins for the services it depends on. An Argusic agent installed it in 8 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
OpenBiliClaw v0.3.218 is fully installed, builds, passes lint, and 1007+ tests pass. CLI commands work. The API server starts and responds to health/init-status endpoints.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 92 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- test_api_weibo.py::test_weibo_share_count_survives_recommendation_and_delight_http_serialization - FakeDatabase.get_delight_candidates missing include_delivered parameter5 minutes
- test_api_app.py::TestBackendAPI::test_runtime_status_endpoint_returns_runtime_summary - install_mode='docker' vs expected 'unsupported' due to /.dockerenv detection
- test_api_degraded_mode.py::test_degraded_init_status_reports_degraded_reason - unsupported_runtime vs expected degraded due to old config format in test fixture
- Install time
- 8 minutes
- Cold machine to finish
- 76 minutes
- Errors hit and fixed
- 3 hit, 3 fixed with no human help
- Model tokens used
- 709,942
- Exact commit tested
- 3c53294e7679
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- How the result was proved
- runs before 2026-09-07 did not record the command used to check the result
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
Return code: 0
The fix works. Let me now generate the final ARGUSIC_RESULT. I have all the information I need:
**Install**: Succeeded. `pip install -e ".[dev]"` completed with all dependencies.
**Launch**: Succeeded - API server starts and responds to endpoints. CLI works (`openbiliclaw --hel…
**Tests**: 1007+ tests pass. I fixed one test (`test_weibo_share_count_survives_recommendation_and_…
**Lint**: Ruff and MyPy both pass.
**Verification**: Mock-based since real API keys are required for end-to-end behavior.
exec
/bin/sh -lc "echo 'ARGUSIC_RESULT: {\"install_succeeded\": true, \"launch_succeeded\": true, \"inst…
succeeded in 0ms:
tokens used
709,942Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Recovered from all 3 errors without a human stepping in, which says the failures are documented well enough to solve.
- Licensed MIT, as reported by its host.
- Measured 4 times, so the result is not a one-off.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Took 8 minutes to install, slower than the median of the 11 comparable projects Argusic has measured.
Of the 12 ai-agent projects Argusic has installed and timed, OpenBiliClaw was the 7th fastest to reach a running state, and 9 of 12 reached one at all.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 2/3 | Runs with mocks | 92.00 | 0.30 | |
| Argusic Runner | 1/3 | Ran out of time | 0.00 | 0.44 | |
| Argusic Runner | 2/3 | Ran out of time | 0.00 | 0.15 | |
| Argusic Runner | 1/3 | Ran out of time | 0.00 | 0.26 |
Topics (from GitHub)
ai-agentbilibilichrome-extensioncontent-discoverycross-platformdeepseek-harnessdouyindshdsh-pluginllmlocal-firstpersonal-aiprivacy-firstpythonrecommendation-systemself-hostedtypescriptxiaohongshuyoutubezhihu
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/openbiliclaw)Questions
- Does OpenBiliClaw run?
- OpenBiliClaw runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 8 minutes, hitting 3 errors on the way, and recorded the session.
- How did Argusic test OpenBiliClaw?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 3c53294e7679. 4 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test OpenBiliClaw?
- The run that produced this verdict cost $0.30: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does OpenBiliClaw take to install?
- 8 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does OpenBiliClaw need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing OpenBiliClaw?
- 3 things broke in the recorded run, and 3 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does OpenBiliClaw compare with the alternatives?
- Of the 12 ai-agent projects Argusic has installed and timed, OpenBiliClaw was the 7th fastest to reach a running state, and 9 of 12 reached one at all.
- Where is the evidence for OpenBiliClaw?
- All 4 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.