jev-social runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 0 minutes, hitting 2 errors on the way, and recorded the session.

How did Argusic test jev-social?

On a fresh, disposable machine, with every command recorded and the repository pinned at commit 2f02e6f4c609. 2 attempts are recorded, and the full method is on the methodology page.

What did it cost to test jev-social?

The run that produced this verdict cost $0.01: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.

How long does jev-social take to install?

0.2 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 jev-social need a GPU?

Not to start. Argusic reached a running state on a machine with no GPU.

What goes wrong when installing jev-social?

2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.

Where is the evidence for jev-social?

All 2 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.

jev-social

Open-source, local-first social media research agent for Instagram, TikTok, and LinkedIn. Jev routes read-only steps; socai CLI captures cited browser evidence.

Runs with mockssource: GitHubJavaScriptMITcommit 2f02e6f4c609

JavaScript, MIT licensed. The project labels itself: agent skills, ai agents, browser agent, browser automation, decision model, deep research, instagram and jev.

jev-social runs, with stand-ins for the services it depends on. An Argusic agent installed it in 0.2 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.

All 253 offline tests pass, the HTTP server starts and responds 200 on /, and the status JSON is correct.
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 86 of 100 (the mean of this project's run scores).

At a glance

verdict: Runs with mocks
Argusic Score: 86 / 100
cost of the verifying run: $0.01 (measured)
recorded runs: 2
last tested: 2026-11-07
stars: 201
forks: 0
open issues: 0
watchers: 0
created: -
last push: -

Subject data from GitHub, linked at the top of this page. 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.

Time lost to each failure while testing jev-social, drawn from the recorded run — Every bar is a failure the agent recorded, with the time it cost. Drawn from this run, not from anywhere else.

What went wrong, in the agent's own words

The agent's own words, worst first, never rewritten into advice.

Node.js was v18 but project requires >=22 (engines.node)3 minutes
Three git-dependent tests failed because immutable release commit SHAs (8369621fd..., 5b8fcf3f...) were not present in the shallow clone1 minute

Install time: under a minute
Cold machine to finish: 3 minutes
Errors hit and fixed: 2 hit, 2 fixed with no human help
How the result was proved: npm test --node-test exited 0, 253 passed; curl http://127.0.0.1:8767/ returned 200; node ./bin/jev-social.js status returned valid JSON
Model tokens used: 88,920
Exact commit tested: 2f02e6f4c609
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

The end of the recording

The last lines of the terminal session that decided this verdict, exactly as they were recorded.

4. **App launch** — `npm start -- status` returns a valid JSON readiness object. `npm start -- serv…
5. **No third-party credentials needed** — The tests are entirely offline (mocked CLI, mocked decis…
2026-11-07T11:33:07.257050Z ERROR codex_core::session: failed to record rollout items: thread 01a1b…
tokens used
88,920
Everything works. Let me compile the results.
**Summary of what happened:**
1. **Install** — `npm ci` succeeded (0 vulnerabilities). The project has no dependencies.
2. **Syntax check** — `npm run check` passed cleanly.
3. **Test suite** — `npm test` initially had 3 failures, all from git commit SHAs (`8369621fd...`, …
4. **App launch** — `npm start -- status` returns a valid JSON readiness object. `npm start -- serv…
5. **No third-party credentials needed** — The tests are entirely offline (mocked CLI, mocked decis…

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

Installed in 0.2 minutes, faster than the median of the 113 comparable projects Argusic has measured.
Recovered from all 2 errors without a human stepping in, which says the failures are documented well enough to solve.
Licensed MIT, as reported by its host.
Measured 2 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.

Of the 114 agent-skills projects Argusic has installed and timed, jev-social was the 11th fastest to reach a running state, and 84 of 114 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	0.01	2026-11-07 11:33 UTC
Argusic Runner	1/3	Unverified	80.00	0.12	2026-11-07 10:41 UTC

Embed the badge

Markdown for the project README. It links back here; terms on the terms page.

[![Tested by Argusic](https://argusic.com/badge/jev-social.svg)](https://argusic.com/subject/jev-social)

Questions

Does jev-social run?: jev-social runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 0 minutes, hitting 2 errors on the way, and recorded the session.
How did Argusic test jev-social?: On a fresh, disposable machine, with every command recorded and the repository pinned at commit 2f02e6f4c609. 2 attempts are recorded, and the full method is on the methodology page.
What did it cost to test jev-social?: The run that produced this verdict cost $0.01: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
How long does jev-social take to install?: 0.2 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 jev-social need a GPU?: Not to start. Argusic reached a running state on a machine with no GPU.
What goes wrong when installing jev-social?: 2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.
How does jev-social compare with the alternatives?: Of the 114 agent-skills projects Argusic has installed and timed, jev-social was the 11th fastest to reach a running state, and 84 of 114 reached one at all.
Where is the evidence for jev-social?: All 2 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.