tick-stock-panel
TSP自托管、零运维的 A 股「自建策略 + 监控 + 回测」量化工作台 | LLM能力驱使策略定制+个股分析+复盘 | 自由接入第三方数据源与个性化扩展数据 | 个人开源
Runssource: GitHubhomepagePythonMITcommit bab609b2d42c
Python, MIT licensed. The project labels itself: a stock, ai agent, aigc, aigc detection, backtesting, daily, duckdb and fastapi.
tick-stock-panel runs. An Argusic agent installed it in 3 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Backend server starts and serves /health (200), /api/capabilities, and /api/auth/status; all 1511 backend tests pass; frontend build succeeds via pnpm build
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 100 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_pipeline_self_heals_snapshot_day: same UTC vs CN_TZ discrepancy — test's CN_TZ today was 2026-09-25 but pipeline's internal date.today() was 2026-09-24, so snapshot partition was treated as 'today' and skipped3 minutes
- test_benchmark_momentum_today_excludes_today_rows: UTC date.today() vs CN_TZ offset caused today filter mismatch (pipeline uses CN_TZ, test used UTC)2 minutes
- test_upsert_edit_invalidates_cache: ExtConfigStore.upsert didn't invalidate _load_all_cache, so load_all returned stale data when mtime_ns didn't change between writes1 minute
- Install time
- 3 minutes
- Cold machine to finish
- 24 minutes
- Errors hit and fixed
- 3 hit, 3 fixed with no human help
- How the result was proved
- pytest tests/ exited 0, 1511 passed, 1 skipped across 51s; 'curl localhost:3018/health' returned 200 with {"status":"ok","version":"0.2.2","mode":"none"}
- Model tokens used
- 292,385
- Exact commit tested
- bab609b2d42c
- 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
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
raw = lf_batch.sort(["symbol", "date"]).collect(streaming=True)
tests/test_data_integrity.py::test_pipeline_self_heals_snapshot_day
tests/test_data_integrity.py::test_pipeline_self_heals_snapshot_day
/work/repo/backend/app/indicators/pipeline.py:1710: DeprecationWarning: the `streaming` parameter…
.collect(streaming=True)
-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
======================= 54 passed, 13 warnings in 1.79s ========================
All done. Here's the final summary:
2026-09-24T22:40:19.641494Z ERROR codex_core::session: failed to record rollout items: thread 01a0d…
tokens used
292,385
All done. Here's the final summary: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
- Reached a running state on a clean machine, with the session recorded.
- Installed in 3 minutes.
- Recovered from all 3 errors without a human stepping in, which says the failures are documented well enough to solve.
- Ran without a GPU, so it does not need one to start.
- Licensed MIT, as reported by its host.
- Measured 3 times, so the result is not a one-off.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
- A quick evaluation: it was running 3 minutes after the clone.
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
Topics (from GitHub)
a-stockai-agentaigcaigc-detectionbacktestingdailyduckdbfastapillmpolarsquantquantitative-tradingreactscreenerstockstock-analysistickflowtradetrainingtsp
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/tick-stock-panel)Questions
- Does tick-stock-panel run?
- Yes. tick-stock-panel runs. Argusic installed and launched it on a clean machine in 3 minutes, hitting 3 errors on the way, and recorded the session.
- How did Argusic test tick-stock-panel?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit bab609b2d42c. 3 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test tick-stock-panel?
- The run that produced this verdict cost $0.13: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does tick-stock-panel take to install?
- 3 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 tick-stock-panel need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing tick-stock-panel?
- 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.
- Where is the evidence for tick-stock-panel?
- All 3 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.