One maintained record
Dates, roles, education, projects, credentials, links, and hard facts stay in one maintained local file.
A concrete example
What goes inside a career context file?
Inspect a fictional template before creating a career context file for AI-assisted work.
The idea
Keep career context in one maintained file.
A personal career context file is an editable local Markdown record for your education, experience, projects, research, skills, certifications, achievements, goals, links, and evidence. Agents read it before working on a CV, LinkedIn profile, GitHub profile, portfolio, application, or interview task.
Visible evidence boundaries
The file tells the agent what is verified, what is only a goal, and which claims it must not invent.
Reuse across tasks
The same facts can support CVs, profiles, portfolios, applications, and interviews without making every output identical.
File anatomy
What the context file stores and why
Each section has a distinct job. Stable headings help humans maintain the file and help agents retrieve only the facts needed for the current task.
Quick reference
A selective YAML snapshot gives an agent current positioning, target roles, strongest skills, credentials, and public links without loading the full history.
Evidence boundary
The scope declaration and verified-facts anchors separate reusable facts from goals, drafts, self-reported details, and claims that still need evidence.
Education and research
Degrees, coursework, theses, publications, and academic projects preserve the detail that usually disappears from a short CV.
Experience and projects
Roles and projects connect responsibilities, technologies, constraints, results, and proof links to a specific source.
Skills and credentials
The skills index, certifications, achievements, and languages stay usable because every important claim is supported elsewhere in the file.
Goals and output rules
Target roles, interests, preferred tone, and claims to avoid tell the agent what direction to support without rewriting aspirations as experience.
Annotated sample file
A complete structure can still be readable.
This fictional example shows the stable structure without exposing a real person's context. Color separates Markdown headings, the YAML quick reference, semantic fields, evidence comments, and ordinary supporting detail.
- Blue headings create stable sections and semantic tags.
- Green YAML keys form the fast, selective summary.
- Gold fields highlight evidence, status, technologies, and constraints.
- Muted comments mark private validation anchors and template notes.
Privacy boundary: the template is public and fictional. Your completed context file should remain private and should never be copied into this website.
Markdown sectionsYAML snapshotEvidence fieldsPrivate comments
# Alex Morgan - Backend developer focused on reliable web services
## QUICK REFERENCE
```yaml
name: Alex Morgan
current_location: Valencia, Spain
target_roles:
- Backend Developer
- Platform Engineer
open_to_relocation: true
positioning_summary: "Backend developer with experience building APIs,
internal tools, and observable web services."
education:
- "BSc Computer Science | Example University | 2025"
professional:
- "Backend Developer Intern | Northstar Labs | Mar-Sep 2025"
top_skills:
- TypeScript
- Node.js
- PostgreSQL
- Docker
- REST APIs
tools:
- GitHub Actions
- OpenTelemetry
- Linux
certifications:
- "Cloud Fundamentals | Example Institute | 2025"
languages:
- "English: C1"
- "Italian: Native"
github: https://github.com/alexmorgan
linkedin: https://linkedin.com/in/alexmorgan
portfolio: https://alexmorgan.dev
```
This file is Alex Morgan's private professional source of truth. It is not a
public CV. Agents use it to create grounded career outputs while keeping goals
separate from completed experience.
<!-- VERIFIED FACTS: degree=2025, internship=2025-03/2025-09 -->
## GOALS AND TARGETING
**Ideal role:** Backend or platform engineer on a product team.
**Want to work on next:** service reliability, internal platforms, and CI/CD.
**Evidence boundary:** Production API work is verified. Platform engineering
is a direction supported by personal projects, not a past job title.
## EDUCATION
### [DEGREE] BSc Computer Science | Example University | 2025
Focus: databases, distributed systems, software engineering, and web services.
#### [COURSE] Distributed Systems | 2025
Topics: replication, consistency, message queues, and fault tolerance.
##### [PROJECT] QueueWatch
**TL;DR:** Dashboard for inspecting background-job failures in a local test environment.
**Description:** Built a searchable failure timeline and retry workflow.
**Technologies:** TypeScript, Fastify, PostgreSQL, OpenTelemetry, Docker.
**Evidence:** Public repository with setup instructions and architecture notes.
## PROFESSIONAL EXPERIENCE
### [ROLE] Backend Developer Intern | Northstar Labs | Mar-Sep 2025
**TL;DR:** Maintained Node.js API endpoints for an internal operations tool.
- Added request validation and integration tests to three existing endpoints.
- Reduced a recurring report from a manual spreadsheet process to one API call.
- Worked with TypeScript, PostgreSQL, Docker, and GitHub Actions.
## RESEARCH AND PUBLICATIONS
### [PREPRINT] Reliable Retry Policies for Background Jobs | Draft
**TL;DR:** Small reproducibility study comparing retry policies under simulated failures.
**Status:** Draft; do not describe as peer reviewed or published.
## SKILLS INDEX
**Languages:** TypeScript, SQL
**Backend:** Node.js, Fastify, REST APIs
**Data:** PostgreSQL
**Infrastructure:** Docker, GitHub Actions, Linux
**Observability:** OpenTelemetry
## CERTIFICATIONS AND ACHIEVEMENTS
### [CERT] Cloud Fundamentals | Example Institute | 2025
Credential ID: EXAMPLE-0001
Evidence: fictional certificate record for template demonstration only.
### [AWARD] University Software Project Showcase | Finalist | 2025
Evidence: fictional event result for template demonstration only.
## LANGUAGES
| Language | Level | Evidence |
| --- | --- | --- |
| Italian | Native | Self-reported |
| English | C1 | Fictional example certificate |
## EXTRACURRICULAR AND LEADERSHIP
### [ORG] University Developer Society | Workshop Volunteer | 2024-2025
- Helped prepare two introductory Git and API workshops.
- Do not describe this as people management or formal teaching employment.
## OUTPUT PREFERENCES
- Use plain language and short sentences.
- Prefer specific examples over broad claims.
- Ask before adding a metric that is not written in this file.
- Keep goals separate from completed experience.
## PUBLIC PROFILE SNAPSHOT
**GitHub:** https://github.com/alexmorgan
**LinkedIn:** https://linkedin.com/in/alexmorgan
**Portfolio:** https://alexmorgan.dev
<!-- FICTIONAL EXAMPLE: Replace every value with verified personal information.
Keep the completed context file private. -->Use it in a normal prompt
The file supplies context. Your prompt supplies the task.
Use the attached personal career context file.
Use the vitaecontext-github skill to review my GitHub profile.
Tell me what to change first and do not add claims that are not in the file.The context file does not publish or optimize anything by itself. It supplies the factual layer; the selected platform skill supplies the rules for a CV, LinkedIn profile, GitHub profile, portfolio, application answer, interview preparation, or another career task.