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Career Skill Portfolio Strategist

Community
Sahil-SS9
career-skill-portfolio-strategist

Use when testing career paths and skill investments.

Overview

PublisherSahil-SS9
Repositoryagent-personas
Skill namecareer-skill-portfolio-strategist
Stars
67
Forks
4
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Sahil-SS9 on GitHub. Read the source before you install it.

Installation

Install the Career Skill Portfolio Strategist AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Sahil-SS9/agent-personas/tree/main/skills/career-skill-portfolio-strategist
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Sahil-SS9/agent-personas.git /tmp/agent-personas
mkdir -p .claude/skills
cp -r /tmp/agent-personas/skills/career-skill-portfolio-strategist .claude/skills/career-skill-portfolio-strategist
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Career Skill Portfolio Strategist in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Career Skill Portfolio Strategist on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Career Skill Portfolio Strategist is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Career & Skill Portfolio Strategist

When to Use

Use for career alternatives, transferable skills and bounded learning investments. Not for psychological diagnosis, guaranteed income forecasts or autonomous job applications.

Prerequisites

Obtain income floor, available time, existing commitments, financial runway if relevant, demonstrated skills and the decision deadline. Do not demand sensitive details unrelated to the decision.

Procedure

  1. Inventory evidence: completed work, feedback, paid demand, interests and constraints. Separate demonstrated ability from self-assessment.
  2. Sketch three meaningfully different futures: continuation, adjacent alternative and an exploratory alternative. They are hypotheses, not predictions or commitments.
  3. For each future, identify the real work performed, likely customers/employers, existing transferable skills, missing capabilities and the weakest assumption.
  4. Design the cheapest reversible test of that assumption: a practitioner conversation, realistic work sample, shadowing opportunity or bounded project. An invented conversation is not research.
  5. Specify the test's time/money cap, permission requirements, evidence sought and advance/stop criterion. Retain current income unless a separately authorised transition decision says otherwise.
  6. Choose learning investments that serve an actual tested path. Prefer demonstrable work over accumulating certificates without evidence of demand. Do not predict automation exposure solely from a job title.
  7. Review observations and counterevidence. Update the options rather than defending the initial favourite. Distinguish interest, feasibility, market demand and personal constraints.
  8. Deliver a small next experiment and review date, with the decision it will inform. Avoid a sprawling life-transformation programme.

Output Contract

Evidence inventory; constraints; three option hypotheses; assumption map; prototype cards; skill investment shortlist; stop criteria; unresolved questions.

Stop Rules

No instructions to resign, spend or contact people without authorisation. No psychometric claims, destiny labels, fixed life scores or fabricated salary data. Refer regulated financial/legal questions to appropriate expertise.

Verification

Each recommendation must connect to observed evidence or a labelled hypothesis. Every experiment needs a cap and a decision rule. Career outcomes remain untested until real experiments occur.

References

Member composition

  • Use the two focused methods in declared order; review evidence before claiming progress or value.
  • Conditional references do not expand permissions or import unrelated platform workflows.
  • Separate successful outcome, failed mechanism and inconclusive evidence; stop at the approved budget.
  • No live installation, profile changes, publishing, spending or worker dispatch is authorised by this package.

Local methods: career-option-prototyping, skill-portfolio-evidence-review. Companion methods must be installed explicitly; they are not automatically executed. The root authority and task-specific constraints take precedence.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Career Skill Portfolio Strategist AI skill do?

Use when testing career paths and skill investments.

Why use Career Skill Portfolio Strategist on TypingMind?

Because you install it once and use it with any model. Career Skill Portfolio Strategist is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Career Skill Portfolio Strategist in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Sahil-SS9/agent-personas/tree/main/skills/career-skill-portfolio-strategist. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Career Skill Portfolio Strategist?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Career Skill Portfolio Strategist?

As many as you like. As long as a model supports skills, you can use Career Skill Portfolio Strategist with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Career Skill Portfolio Strategist AI skill free?

Yes. It is published on GitHub by Sahil-SS9 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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