Who it is for
- AI/frontend candidates with weak public proof
- Angular and TypeScript engineers repositioning toward AI product work
- People who need stronger GitHub, portfolio, and interview evidence
v0.2.0 - local-first - proof-first - MIT
The proof-before-applying engine for AI/frontend pivots.
Occupation-Ops turns vague experience into recruiter-readable public proof. It is not a mass-apply tool, not a scanner, and not a tracker.
Built for candidates who need stronger proof before more outreach.
No SaaSNo API key requiredJSON + Markdown + HTMLTheme toggle included
npm run gap:role
INPUT
$profile.yml
track: ai-frontend-architect - rubric-driven
OUTPUT BUNDLE
OKrole-gap-analysis.md
OKrole-gap-analysis.json
OKrole-gap-analysis.html
OKweekly-proof-plan.md
OKprofile-audit.json
DOSSIER SECTIONS
Proof inventoryRole-gap scorecardGitHub rewriteREADME checklistPortfolio briefInterview story mapWeekly shipping plan
Local-first CLINo API key requiredTruthfulness guardrailsMarkdown + JSON + HTMLGitHub Pages docs
Quick Start
Up and running in 60 seconds.
The website explains the system. The terminal does the work. The flagship command generates a full proof dossier with Markdown, JSON, and HTML outputs.
quick-start.sh
$git clone https://github.com/AnkitParekh007/occupation-ops.git
$cd occupation-ops && npm install
$npm run init
$npm run gap:role
OKoutput/role-gap-analysis.md
OKoutput/role-gap-analysis.json
OKoutput/role-gap-analysis.html
Ideal User
LinkedIn visitors should understand in 20 seconds whether this is for them.
Occupation-Ops is most valuable when the candidate problem is weak public proof, not weak application volume.
Who it is not for
- Mass-apply operators
- Portal scraping workflows
- Recruiter CRM users
- Anyone looking for fake resume inflation
What you should expect
- A visible scorecard of current proof
- A backlog of missing recruiter signals
- A tighter GitHub and README positioning plan
- A concrete weekly proof-shipping plan
Documentation
GitBook-style docs, but aligned to the actual repo workflow.
The docs are structured around how developers use and extend the repo: onboarding, CLI usage, rubrics, output bundles, and architecture.
Quick Start
Clone, install, run one command, and open the flagship proof dossier in your browser.
Open docs ->CLI Reference
The product surface is the terminal. Every core command has a concrete output bundle.
Open docs ->Developer Docs
Architecture, rubric structure, validators, and extension points for contributors.
Open docs ->Sample Dossier
See the flagship output bundle before cloning the repo.
Open docs ->How It Works
The workflow is simple enough to try and opinionated enough to be useful.
This is not a chat prompt wrapper. The output is a rubric-scored dossier with explicit proof signals.
Describe the current proof state
Fill in profile.yml with your current positioning, links, skills, and proof artifacts.
Run the flagship command
Occupation-Ops scores the profile against a rubric, not just generic prose templates.
Review the dossier
Open the HTML output to see score, gaps, validators, and backlog in one place.
Ship stronger public evidence
Use the GitHub rewrite, project briefs, and weekly plan to improve what recruiters actually see.
Real Output
Show the product, not just the category story.
The launch surface now includes actual dossier visuals so cold visitors can judge the output quality quickly.
Flagship dossier overview
One HTML report that shows score, proof backlog, GitHub rewrite, validators, and weekly plan.
Role-gap scorecard
The core evaluation is explicit about what is supported, what is missing, and what to improve next.
Positioning
Occupation-Ops is not trying to be a job-search pipeline.
The competitive advantage is narrower and stronger: help AI/frontend candidates build proof before they apply, so their GitHub, portfolio, and interview narratives hold up.
What it is not
- Mass apply automation
- Portal scanning or scraping
- ATS gaming or fake metrics
- Recruiter CRM workflows
What it is
- Proof inventory and evidence scoring
- GitHub and README positioning guidance
- Portfolio project planning
- Interview-safe story construction
Launch with a concrete sample, not an abstract promise.
The AI Frontend Architect dossier is the wedge. The homepage, docs, sample outputs, and launch assets should all make that visible within one screen.