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Agent skill

Star Story Extraction

by DanielPodolsky in DanielPodolsky/ownyourcode

Transforms completed work into STAR interview stories (Situation, Task, Action, Result).

MITAuto-check passedBusiness, Finance & HR

Install Star Story Extraction

skills CLI
$ npx skills add DanielPodolsky/ownyourcode --skill star-story-extraction -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install DanielPodolsky/ownyourcode star-story-extraction --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/DanielPodolsky/ownyourcode.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/career/star-stories .claude/skills/star-story-extraction && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
star-story-extraction
GitHub stars
290
Used in
1 other repo
Token cost
~1.4k tokens
SKILL.md length
604 words
Files
1
Skills in repo
19
Repo updated
First seen
Licence
MIT

At a glance

Transforms completed work into STAR interview stories (Situation, Task, Action, Result).

  • Works in 2 steps: Identify the Story Type → Guide Through STAR
  • Completing tasks
  • SKILL.md covers Purpose, The STAR Method, Extraction Flow and Story Quality Checklist, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Star Story Extraction is an agent skill from DanielPodolsky/ownyourcode. Transforms completed work into STAR interview stories (Situation, Task, Action, Result). Use when completing tasks, preparing for behavioral interviews, or documenting achievements.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Interview preparation. The repository describes itself as: Claude Code workflow for AI-mentored development. Work efficiently with Spec-Driven Development and the 6 Gates. Built to fight cognitive offloading — for developers using AI to… The licence is MIT.

When your agent uses it

  • Completing tasks
  • Preparing for behavioral interviews
  • Documenting achievements

Example prompts

  • “Use the star-story-extraction skill to transform completed work into STAR interview stories (Situation, Task, Action, Result)”
  • “/star-story-extraction”

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Identify the Story Type
  2. Guide Through STAR

What it can do on your machine

Read from SKILL.md and the folder at commit bd1f17c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Star Story Extraction loads about 1.4k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 604 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from DanielPodolsky/ownyourcode at commit bd1f17c, republished under its MIT licence (© DanielPodolsky). 604 words, ~1,411 tokens.

Download SKILL.mdSave it as .claude/skills/star-story-extraction/SKILL.md (or your agent's skills folder).
name
star-story-extraction
description
Transforms completed work into STAR interview stories (Situation, Task, Action, Result). Use when completing tasks, preparing for behavioral interviews, or documenting achievements.

STAR Story Extraction

"Every feature you build is an interview answer waiting to be told."

Purpose

Transform completed work into compelling interview stories using the STAR method. These stories demonstrate real problem-solving ability.

The STAR Method

ComponentQuestionFocus
Situation"What was the context?"Set the scene, explain the problem
Task"What were YOU responsible for?"YOUR specific role and responsibility
Action"What did YOU do?"Specific technical actions YOU took
Result"What was the outcome?"Impact, metrics, improvements

Extraction Flow

Step 1: Identify the Story Type

What kind of problem did you solve?

Story TypeGood For Questions Like
Technical challenge"Tell me about a difficult bug you solved"
Feature implementation"Describe a feature you're proud of"
Performance optimization"How did you improve system performance?"
Security fix"Tell me about a security issue you addressed"
Refactoring"Describe a time you improved code quality"
Learning curve"Tell me about a time you learned something quickly"
Step 2: Guide Through STAR
Situation (2-3 sentences)

"What was the context? What problem or challenge existed before you started?"

Good elements:

  • Business context (why it mattered)
  • Technical constraints
  • Scale/impact of the problem

Avoid:

  • Too much background
  • Irrelevant details
  • Blaming others
Task (1-2 sentences)

"What were YOU specifically responsible for? What was your role?"

Good elements:

  • Clear ownership
  • Specific scope
  • Why you were the one to do it

Avoid:

  • "We did this" (use "I")
  • Vague responsibilities
Action (The meat - 3-5 sentences)

"Walk me through the specific steps YOU took. Be technical."

Good elements:

  • Specific technologies used
  • Problem-solving approach
  • Trade-offs considered
  • Technical decisions made

Avoid:

  • Glossing over the how
  • Buzzword soup
  • "I just implemented it"
Result (1-2 sentences)

"What was the outcome? Can you quantify the impact?"

Good elements:

  • Metrics where possible (50% faster, 0 bugs in production)
  • Business impact
  • What you learned

Avoid:

  • "It worked" (too vague)
  • No mention of impact

Story Quality Checklist

  • Uses "I" not "we" (shows ownership)
  • Includes specific technologies
  • Demonstrates problem-solving
  • Shows technical depth
  • Has measurable result if possible
  • Is 2-3 minutes when spoken
  • Answers the implied "why hire you?"

Story Template

markdown
# STAR Story: [Feature/Problem Name]

**Date:** [When completed]
**Type:** [Technical Challenge / Feature / Performance / Security / Refactor]

## Situation
[The context. What problem existed? Why did it matter?]

## Task
[YOUR specific responsibility. What were YOU asked to do?]

## Action
[The specific steps YOU took. Be technical. Show your thought process.]

## Result
[The outcome. Metrics if possible. What impact did it have?]

---

## Interview Variations

This story can answer:
- "Tell me about a time you [X]"
- "Describe a challenging [Y] you worked on"
- "How did you approach [Z]?"

## Key Technical Points to Mention
- [Technology/pattern 1]
- [Technology/pattern 2]
- [Decision/trade-off made]

Example: Good vs Bad STAR

Bad Story

"I built a login form. It had validation. It worked."

Problems: No context, no challenge, no depth, no impact.

Show full SKILL.md (237 more words)Show less
Good Story

Situation: Our SaaS application was experiencing a 40% drop-off during signup because the existing form had poor UX and no real-time validation, frustrating users.

Task: I was responsible for rebuilding the entire authentication flow, focusing on reducing friction while maintaining security.

Action: I implemented a multi-step form with real-time validation using React Hook Form for performance. I added JWT authentication with secure refresh token rotation to handle long sessions. The key challenge was balancing security (short token expiry) with UX (no jarring logouts), which I solved by implementing silent refresh 5 minutes before expiry.

Result: Sign-up completion improved by 35%, and we've had zero authentication-related security incidents since launch. The pattern I built is now used across our other products.

Socratic Story Questions

Guide the junior with these:

  1. Finding the story: "What was the hardest part of this feature?"
  2. Adding depth: "Walk me through your debugging process when X happened."
  3. Showing ownership: "What decision did YOU make that shaped this?"
  4. Quantifying results: "How would you measure the impact of this work?"
  5. Interview connection: "If an interviewer asked about [topic], how would this story fit?"

Common Story Mistakes

MistakeFix
"We built..."Use "I implemented..."
Too long (10+ minutes)Cut to 2-3 minutes
No technical depthAdd specific technologies and decisions
No resultAlways end with impact
Only happy pathInclude challenges overcome

Save Location

Stories are saved to:

ownyourcode/career/stories/[date]-[feature-name].md

Example: ownyourcode/career/stories/2026-01-15-jwt-auth.md

© DanielPodolsky, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/career/star-stories of DanielPodolsky/ownyourcode.

Open the folder on GitHubat commit bd1f17c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in DanielPodolsky/ownyourcode, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Star Story Extraction next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Leetcode Pywislertt/leetcode-py142—~1.4kAutomated safety check: PassApache-2.0
Java Backend InterviewerSnailclimb/interview-guide3.3k—~132Automated safety check: PassAGPL-3.0
Binary Trees InterviewerPrepLabsAI/InterviewMentor112—~2.4kAutomated safety check: PassMIT

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Categories

Questions about Star Story Extraction

What does Star Story Extraction do?

Transforms completed work into STAR interview stories (Situation, Task, Action, Result). Star Story Extraction is an agent skill from DanielPodolsky/ownyourcode. Transforms completed work into STAR interview stories (Situation, Task, Action, Result).

When should I use Star Story Extraction?

Star Story Extraction fits situations like: completing tasks; preparing for behavioral interviews; documenting achievements.

How do I install Star Story Extraction in Claude Code?

Run `npx skills add DanielPodolsky/ownyourcode --skill star-story-extraction -a claude-code`. Or copy the skill folder (.claude/skills/career/star-stories in DanielPodolsky/ownyourcode) into .claude/skills/star-story-extraction in your project. Claude Code loads it when a task matches its description.

How do I install Star Story Extraction in Codex?

Run `npx skills add DanielPodolsky/ownyourcode --skill star-story-extraction -a codex`. Or copy the skill folder (.claude/skills/career/star-stories in DanielPodolsky/ownyourcode) into .agents/skills/star-story-extraction in your project. Codex loads it when a task matches its description.

Can I use Star Story Extraction in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add DanielPodolsky/ownyourcode --skill star-story-extraction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/star-story-extraction, .gemini/skills/star-story-extraction, .github/skills/star-story-extraction and .opencode/skills/star-story-extraction in your project.

What does Star Story Extraction need to run?

SKILL.md names no scripts, command-line tools or credentials: Star Story Extraction is instructions for the agent only.

Does Star Story Extraction access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Star Story Extraction safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Star Story Extraction use?

Star Story Extraction is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Star Story Extraction use?

About 1.4k tokens (SKILL.md is roughly 5.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Star Story Extraction?

Skills that share tags, products or a category with Star Story Extraction: Algo Sensei (karanb192/algo-sensei, 286 stars), Backend and Agent Project Selector (lishuangqiang/backend-agent-resume-scout, 350 stars), Leetcode Py (wislertt/leetcode-py, 142 stars) and Java Backend Interviewer (Snailclimb/interview-guide, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Star Story Extraction?

DanielPodolsky (a GitHub user) maintains it in DanielPodolsky/ownyourcode, which has 290 GitHub stars. The repository holds 19 skills in this directory. The repository was last updated on June 27, 2026.

Source: DanielPodolsky/ownyourcode on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.