Bilingual positioning workspace
Review an evidence-bounded headline, About copy, Featured text and three positioning pillars in Persian or English.
Professional growth · Case study Completed
LinkedIn Growth System
A human-approved workspace for evidence-led professional communication.
LinkedIn Growth System v1.0.1 organizes positioning, an eight-post editorial calendar, a strict review sequence, a small interaction demo and an unknown-first KPI loop. It prepares and validates material locally; every LinkedIn-facing action remains manual.
The public runtime for this project is temporarily unavailable.
TypeScript · Vite · Vitest · Browser APIs
- Mohammed Mahdi Kaabi’s role
- Product strategy, evidence review, interaction design and frontend implementation.
- Product version
- 1.0.1 · Completed
- Interface and content
- Persian and English UI · canonical publication copy in English
The problem
Professional publishing often mixes positioning, evidence, approval and performance tracking in one opaque process. This product keeps those steps visible and refuses to turn missing evidence into invented claims or engagement numbers.
What is implemented
Eight-post calendar
Inspect eight English drafts with dates and source links. Every draft begins publication-blocked and follows an explicit review sequence.
Human approval workflow
Move a draft through operator preparation, Critic review, user approval, local export, manual publication and outcome recording.
Signal Match demo
Run a two-minute shape-matching interaction that keeps score and timer only in current page memory and makes no clinical or research claim.
Unknown-first KPI loop
Validate seven metrics from manual form entries or a selected CSV, or reference a local screenshot without uploading, reading or storing it.
A deliberately local product boundary
The public build packages the original Vite interface as an isolated static application. It uses browser memory for workflow and demo state and a namespaced localStorage key only for the language preference. There is no LinkedIn login, scraping, browser control, unofficial API, auto-publishing, messaging or fabricated engagement data.
- Review positioning and evidence
- Review a publication-blocked draft
- Approve and export locally
- Publish manually and record the outcome
04 · Evidence
What the repository establishes
The inspected 0.1.0 package and product documents identify the UI as LinkedIn Growth System v1.0.1. The executable source includes complete Persian and English localization, eight sourced drafts, the approval state machine, local export, Signal Match, KPI parsers and responsive styles. Focused product tests for growth and localization passed; the production frontend build and repository secret/policy scanners also passed.
Source revision 7992ba2 · 2026-08-30
Boundaries of the current product
- It does not sign in to LinkedIn, edit a profile, scrape pages, send messages, create connections or publish content.
- Draft workflow and KPI values are not persisted; refreshing the page resets them. Only the language preference is saved locally.
- The screenshot input is a local reference only: the app does not upload, OCR, inspect or retain the image.
- The preserved D1/import and frozen authentication work are outside this public frontend and are not presented as live capabilities.
- Signal Match is a design demo, not a clinical, cognitive, educational or research assessment.
Assets and third-party material
No root LICENSE file is present, so the repository is not presented as generally redistributable. This authorized portfolio build contains no third-party image, music, video, dataset or LinkedIn brand asset. Vite and the bundled runtime retain their package licenses.
Third-party noticesOpen the growth workspace
Switch between Persian and English, inspect the manual workflow and try Signal Match. No LinkedIn account or API key is requested.
The public runtime for this project is temporarily unavailable.