# How to Add Custom STAR Stories to the Career-Ops Interview Story Bank > Easily add custom STAR stories to your Career-Ops interview story bank. Learn the STAR+R format to effectively showcase your experience and prepare for interviews. - Repository: [Santiago Fernández de Valderrama/career-ops](https://github.com/santifer/career-ops) - Tags: how-to-guide - Published: 2026-07-03 --- **To add custom STAR stories to the Career-Ops interview story bank, create or edit the [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) file and format each narrative using the STAR+R (Situation–Task–Action–Result–Reflection) template under top-level headings.** Career-Ops maintains a centralized **story bank** to store your behavioral interview narratives. When you run any interview-related mode—such as `interview/plan`, `interview/practice`, or `interview/debrief`—the system reads from [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) and injects your stories into block F of the evaluation report. This guide explains how to populate that file with your own STAR+R examples. ## Where Career-Ops Stores the Interview Story Bank The repository expects your custom narratives in a specific location. According to the source code in [`modes/_shared.md`](https://github.com/santifer/career-ops/blob/main/modes/_shared.md), the file [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) is declared as a trusted source for interview-related modes. When you execute an interview preparation command, the interpreter looks for this exact path. If the file is missing, the system proceeds without custom stories. The architecture diagram in [`docs/ARCHITECTURE.md`](https://github.com/santifer/career-ops/blob/main/docs/ARCHITECTURE.md) illustrates this as block F: "Interview prep (STAR stories)"—the pipeline that feeds your prepared examples into planning and practice sessions. Key files involved in this workflow: - [`interview-prep/README.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/README.md) — Documents the purpose of the story bank - [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) — Your editable repository of STAR+R narratives - [`modes/interview/plan.md`](https://github.com/santifer/career-ops/blob/main/modes/interview/plan.md) — References the story bank when building pre-interview strategies - [`modes/interview/practice.md`](https://github.com/santifer/career-ops/blob/main/modes/interview/practice.md) — Pulls stories to suggest stronger answers during mock sessions ## Step-by-Step: Adding Custom STAR+R Stories ### Create the story-bank.md File Begin by creating the file at [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md). This path is hardcoded into the Career-Ops workflow; deviating from this location means the parser will not discover your content. The [`interview-prep/README.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/README.md) file explains that this directory houses all preparation materials, and the story bank specifically holds your behavioral examples for consistent reference. ### Format Stories with the STAR+R Template Each story must begin with a top-level Markdown heading (e.g., `## Story 1 – Launching a ML Pipeline`). Headings serve as delimiters that allow the parser to split individual narratives and enable easy navigation. Beneath each heading, follow the **STAR+R** structure: - **Situation** — Context of the challenge - **Task** — Your specific responsibility - **Action** — Steps you took, ideally with bullet points - **Result** — Quantified outcomes and achievements - **Reflection** — Lessons learned and insights gained Optionally, include an HTML comment identifier like `` immediately after the heading. This convention allows other modes to reference specific stories by ID during debriefs or planning sessions. ### Verify Integration with Interview Modes Once saved, your stories automatically flow into the interview preparation pipeline. The system reads the file at runtime, so any changes reflect immediately without requiring a restart. During report generation, Career-Ops selects the 5–10 most relevant stories from your bank to populate the evaluation, following the "6-10 STAR+R stories" rule referenced in [`modes/oferta.md`](https://github.com/santifer/career-ops/blob/main/modes/oferta.md). ## Complete STAR+R Story Example Copy this template into [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) and customize it with your experience: ```markdown ## Story 1 – Launching a Machine-Learning Pipeline **Situation** Our team needed to replace a legacy ETL process with a scalable, reproducible pipeline for nightly model training. **Task** I was the lead engineer responsible for designing the end-to-end workflow and ensuring zero-downtime migration. **Action** - Chose Airflow for orchestration and Docker for containerisation. - Implemented data validation with Great Expectations, cutting downstream errors by 40%. - Added automated testing in CI; each commit ran a full pipeline dry-run. **Result** - Reduced data-processing time from 6 hours to 45 minutes. - Cut cloud costs by 30% after the first month. - The pipeline handled a 3× increase in data volume without any failures. **Reflection** The biggest lesson was the importance of early-stage data validation; it prevented expensive re-runs later and gave stakeholders confidence in the new system. ``` Add as many stories as needed; the parser ignores any stray text that falls outside heading blocks. ## Managing and Updating Your Story Bank ### Editing Existing Stories To modify a narrative, locate the corresponding heading in [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) and update the content. Because Career-Ops reads the file at runtime, saved changes take effect immediately the next time you invoke `interview/plan` or `interview/practice`. ### Removing Stories Delete the entire heading block, including the STAR+R content beneath it. The parser skips sections without headings, effectively removing those stories from the available pool. ## Summary - **Location matters**: Store custom STAR stories in [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) exactly as referenced in [`modes/_shared.md`](https://github.com/santifer/career-ops/blob/main/modes/_shared.md). - **Structure consistently**: Use top-level headings (`##`) followed by the STAR+R template (Situation, Task, Action, Result, Reflection). - **Optional identifiers**: Add HTML comments like `` for cross-referencing in debriefs. - **Immediate updates**: Changes reflect at runtime without restarting the system. - **Automatic selection**: The system pulls 5–10 relevant stories from your bank for each interview preparation report. ## Frequently Asked Questions ### What file format does the story bank use? The story bank uses standard Markdown (`.md`) format. The parser specifically looks for `##` headings to delineate individual stories and expects the STAR+R sections to follow as bolded subheadings or plain text beneath each heading. ### How many stories should I store in the bank? Career-Ops automatically selects the 5–10 most relevant narratives for any given interview session, following the "6-10 STAR+R stories" guideline found in [`modes/oferta.md`](https://github.com/santifer/career-ops/blob/main/modes/oferta.md). While there is no strict upper limit, maintaining 10–15 diverse examples ensures coverage across different competency areas without overwhelming the selection algorithm. ### Can I link stories to specific debrief sessions? Yes. By adding HTML comment identifiers such as `` immediately after your story headings, you create referenceable anchors. Other modes can then cite these IDs to pull specific stories into post-interview debriefs or forward-looking preparation plans. ### Do I need to restart Career-Ops after updating stories? No. The system reads [`interview-prep/story-bank.md`](https://github.com/santifer/career-ops/blob/main/interview-prep/story-bank.md) at runtime whenever you execute an interview-related mode. Simply save your changes to the file, and the updated content will be available immediately for the next `interview/plan`, `interview/practice`, or `interview/debrief` command.