How does Portfolio Harness differ from just asking a standard chatbot to write my resume?

Generic AI prompts often create "fluff" or hallucinated results; this skill uses a structured interviewing process and specialized layout scripts to ensure every project claim is backed by technical evidence and formatted perfectly for recruiters.

What specific assets are included in the purchase?

You will receive the structured interview logic, the Markdown-to-PDF engine, Python/Node.js scripts for layout validation, and A4-optimized design templates specifically tailored for technical roles.

Are there any specific technical requirements to run the PDF generation?

The skill requires a local environment capable of running Python and Node.js to execute the automated PDF generation and visual measurement scripts included in the package.

Can I use this if I already have a messy GitHub profile but no formal portfolio?

Yes, the skill is designed to audit your existing GitHub repositories or project folders, identifying missing metrics and technical gaps before the writing process begins.

Does the final output follow a standard professional format?

While the logic is optimized for technical depth, the final PDF generation scripts are set to standard A4 dimensions, ensuring your portfolio is print-ready and compatible with common applicant tracking systems (ATS).

portfolio harness

Example session with this skill installed

I want to create a portfolio for a Junior Backend Developer role. I have three projects on GitHub: a chat app, a weather API, and a CLI tool. Help me start the interview and collect facts.

Read your context and instructions
Compiled the portfolio harness

Summary

Reviewed the three projects you listed and found that none of them has a recorded metric yet. Before anything goes into the portfolio, I need facts from you — I won't fill in numbers you haven't measured.

Fact check

Project	What's confirmed	What's missing
Chat app	Stack: Node.js, Socket.io (from package.json)	Your role, the hardest problem, any measured result
Weather API	Stack: FastAPI, PostgreSQL (from requirements.txt)	Why caching was added, before/after numbers
CLI tool	Stack: Go (from go.mod)	Who used it, what it replaced

Interview — round 1

Chat app: Was this a team project? Which parts did you build yourself?
Chat app: What broke or got slow, and how did you notice?

Weather API: Did you measure anything before and after a change (response time, external calls, errors)? If not, can you run a quick test now?
4. CLI tool: Is it used by anyone besides you?

If you don't have a number for something, say so — I'll describe it without a metric rather than guess one.

Next steps

Answer the four questions above (rough answers are fine).
I'll save confirmed facts to records/ and only then move to layout design.

Node.js, Socket.io (from package.json

Connects securely to your tools. The creator never sees your data.

About this skill

Student portfolios often suffer from vague claims, missing metrics, and poor layout. This skill enforces a rigorous, evidence-based workflow to transform raw project data into a professional A4 PDF portfolio. It prioritizes technical decision-making and verified results over generic descriptions, ensuring every project entry stands up to recruiter scrutiny.

What it does

Evidence-based auditing identifies gaps in existing project records to ensure every claim is backed by facts.
Structured interviewing extracts specific technical trade-offs, individual contributions, and measurable outcomes.
Visual analysis critiques provided design references or proposes readable, tech-focused layouts.
Automated PDF generation builds the final document using internal scripts for layout and image verification.
Quality assurance review checks the final PDF for text readability, page overflow, and factual consistency.

How it works

Assessment: Inspects existing project folders or resumes to determine what can be reused.
Fact Collection: Executes a targeted interview to fill information gaps regarding roles and results.
Design Selection: Analyzes design references or proposes A4-optimized structures.
Build: Runs make_pdf.py and measure.js to generate and validate the document.
Review: Audits the output against professional criteria to fix layout or content issues.

Frameworks & tools

Uses Python for PDF generation and image checking, Node.js for layout measurement, and Markdown for intermediate record keeping.

Why this beats prompting it yourself

Generic prompts often hallucinate achievements or use flowery language that recruiters ignore. This skill uses a multi-stage verification process and specialized scripts to ensure the output is technically accurate, properly formatted for A4, and free of layout errors.

Use cases

Converting a messy GitHub profile into a structured PDF for internship applications.
Improving an existing portfolio by adding technical depth and trade-off analysis.
Preparing for technical interviews by documenting project challenges and metrics.

Known limitations

Requires a local environment capable of running Python and Node.js scripts. PDF generation depends on specific bundled scripts and local file system access.

How to use

Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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portfolio harness