Jev Social

Overview

Jev Social turns a natural-language social research goal into bounded Jev routing decisions, then delegates platform-read-only browser work to the local socai CLI. Use the captured posts, profiles, comments, videos, and opened details to produce a compact, source-linked report instead of exposing raw CLI output. "Read-only" means no social-account mutation; the CLI still writes private local run records and may download requested media.

The executable examples below are pinned to the tested runtime commit included in Jev Social v0.1.10. A pin improves reproducibility but is not a trust guarantee; keep the package, browser data, and returned content inside the safety boundaries below.

When to Use

• Use when a user requests evidence-backed research on Instagram, TikTok, or LinkedIn and wants real public posts or profiles rather than a general web summary.
• Use when the user wants a fast demonstration with streamed progress, previewable post or video cards, and a final research report.
• Use when the local socai CLI and the requested platform both pass the Jev Social readiness check.
• Do not use for publishing, commenting, liking, following, messaging, account growth automation, or unrelated web research.

Prerequisites

The workflow requires:

1. Node.js and npx.
2. A configured decision provider: either a user-provided OpenRouter API key with Jev access or a user-started TypeSafe-compatible server on the exact loopback /v1/systemone endpoint. OpenRouter calls may incur provider charges; the loopback provider does not require or receive the OpenRouter key. Set OPENROUTER_REPORT_MODEL=off when report generation must stay on the deterministic evidence path.
3. An installed socai CLI with support for the requested platform.
4. A Chrome session the user is already authorized to use.

If the exact pinned package is not already available locally, explain that the next command downloads and executes the reviewed commit, then obtain explicit user approval before the first fetch. Do not replace the commit with main, latest, or an unreviewed tag.

How It Works

Step 1: Check readiness

Run the status command before every research task:

npx github:socai-io/jev-social#baf3cd6aa4f9c881665c29ed29a10391f761760b status

Require all of the following before continuing:

• The selected decision provider is configured without revealing its key or loopback endpoint. A configured local provider does not require an OpenRouter key. The status command does not probe provider connectivity; if the later research call cannot reach the provider, stop and report that runtime gate without exposing connection details.
• socai is installed and executable.
• The requested platform reports supported.
• The browser boundary matches the user's existing authorized local session.

Treat status output as local diagnostics. Never reproduce configuration paths, executable paths, environment values, credentials, CDP endpoints, or browser-profile details in the answer.

If setup is missing, identify only the missing prerequisite and stop. Do not run this release's automatic onboarding or installer from the catalog skill: its optional socai installation path follows a moving releases/latest URL. Have the user configure the selected provider and install a separately reviewed, pinned socai release outside this workflow. Never place an API key in a command, transcript, report, issue, or committed file.

Step 2: Run bounded research

Use the platform named by the user. Otherwise leave routing to Jev with auto. Preserve the user's natural-language goal, including evidence needs and stopping conditions.

Pass the goal as one argument with an argv-capable process runner; never construct a shell command by interpolating user-supplied text:

program: npx
argv:
  - github:socai-io/jev-social#baf3cd6aa4f9c881665c29ed29a10391f761760b
  - search
  - <exact research goal as one argument>
  - --platform
  - <auto|instagram|tiktok|linkedin>
  - --limit
  - "4"
  - --max-steps
  - "12"

Use --limit 4 for a quick demonstration unless the user asks for broader coverage. Increase --max-steps only when the requested coverage needs more searches, profile reads, post reads, comments, or media operations. The supported ranges are 1-100 results and 1-30 steps.

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