Easel
An open-source AI agent for social media, discover trends, create content, publish everywhere, and learn what works across Xiaohongshu, Douyin, Zhihu, Bilibili, and more.🎨一个开源的 AI 社交媒体智能体, 发现热点趋势、创作内容、一键发布至各大平台，并学习分析哪些内容真正有效，覆盖小红书、抖音、知乎、哔哩哔哩等平台。
Runs with mockssource: GitHubhomepagePythonApache-2.0commit ed05c2b18893
Python, Apache-2.0 licensed. The project labels itself: agent, agent skill, content automation, content creation, content generation, mcp, openclaw and social media.
Easel runs, with stand-ins for the services it depends on. An Argusic agent installed it in 20 minutes and hit 4 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Easel CLI installed in .venv, all 722 tests pass, web app serves HTTP 200 on port 7860 with API and frontend, OpenClaw gateway on port 37289 routed to mock Anthropic API and responded to agent calls
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.
- Node.js 18.19.1 too old (OpenClaw requires 24.16+)6 minutes
- npm install -g openclaw used system node (18.19.1) not our Node 243 minutes
- Python environment externally-managed (Debian), pip install failed2 minutes
- test_bootstrap_requires_both_env_and_route fails when .env has EASEL_CHAT_TRANSPORT=api (test isolation gap)
- Install time
- 20 minutes
- Cold machine to finish
- 21 minutes
- Errors hit and fixed
- 4 hit, 4 fixed with no human help
- How the result was proved
- python -m pytest tests/ -v --tb=short exited 0, 722 passed, 2 skipped, 0 failed
- Model tokens used
- 105,283
- Exact commit tested
- ed05c2b18893
- 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.
- 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
Watch the session
The whole run, from a clean machine, at the speed it actually happened. Nothing is cut and nothing is sped up.
A recording of attempt 1, run , the attempt that decided the verdict above. The terminal recording it was made from is the evidence, stored with a sha256 fingerprint; the video is a rendering of it. Nothing loads from the video host until you press play.
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
# Kill it pkill -f "easel web" 2>/dev/null; pkill -f "uvicorn" 2>/dev/null; sleep 1 echo "=== Final Summary ===" echo "Install: Succeeded" echo "Tests: 722 passed, 2 skipped" echo "Web app: HTTP 200 on root and API" echo "Doctor: all checks pass with mock API configured" echo "Gateway: verified working with mock Anthropic API"' in /work/repo exited 143 in 5008ms: 200 tokens used 105,283
Replay 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 4 errors without a human stepping in, which says the failures are documented well enough to solve.
- Licensed Apache-2.0, as reported by its host.
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 20 minutes to install, slower than the median of the 96 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 97 agent projects Argusic has installed and timed, Easel was the 79th fastest to reach a running state, and 66 of 97 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 | 1/3 | Runs with mocks | 92.00 | 0.23 |
Topics (from GitHub)
agentagent-skillcontent-automationcontent-creationcontent-generationmcpopenclawsocial-mediasocial-media-management
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/easel)Questions
- Does Easel run?
- Easel runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 20 minutes, hitting 4 errors on the way, and recorded the session.
- How did Argusic test Easel?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit ed05c2b18893. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test Easel?
- The run that produced this verdict cost $0.23: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does Easel take to install?
- 20 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 Easel need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing Easel?
- 4 things broke in the recorded run, and 4 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does Easel compare with the alternatives?
- Of the 97 agent projects Argusic has installed and timed, Easel was the 79th fastest to reach a running state, and 66 of 97 reached one at all.
- Where is the evidence for Easel?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.