Prompt personalisation¶
Career tracks¶
Location:
job_hunt/prompts/career/careers.md
Defines every career label the LLM may assign to a job posting, and that
you pass with --career / -cp to daiana save, daiana show,
and daiana update.
{
"options": ["data", "backend", "product"]
}
Each label maps to its own CSV tracker file (e.g. job_tracking_data.csv)
and to a \body<label> command in variants_cl.tex.
Note
Adding a label here without adding \body<label> in variants_cl.tex
will cause a LaTeX compile error on cover letter jobs with that career.
Skills inventory (AI payload)¶
Location:
job_hunt/prompts/skills/skills_payload.md
This file defines the technical “DNA” the LLM scans when selecting skills for your CV. It is structured into categories that map directly to the cvitem structure in your LaTeX templates.
Format: JSON-like structure where each category defines label, max_items, and a list of items with associated keywords for semantic matching.
Backend & Architecture: Python (FastAPI, Django, Flask),
Distributed Systems (gRPC, RabbitMQ, Kafka), Cloud Native (AWS Lambda, Docker, Kubernetes),
Microservices design, System Scalability, Event-driven architecture.
Data Engineering & ML: SQL (PostgreSQL, Redshift),
NoSQL (Redis, MongoDB), Big Data (Apache Spark, Airflow), ETL pipeline design,
MLOps (MLflow, Kubeflow), Model deployment, Feature stores.
DevOps & Infrastructure: Infrastructure as Code (Terraform, Pulumi),
CI/CD (GitHub Actions, GitLab CI), Monitoring & Observability
(Prometheus, Grafana, ELK Stack),
Linux Kernel tuning, Network security, Git workflow optimization.
Languages & Tools: Python, Rust, Go, TypeScript, C++,
Bash, SQL, LaTeX, VS Code, IntelliJ, Jira, Agile/Scrum.
How it works during Oracle:
The LLM parses this payload and compares your items’ keywords against the job description text.
It ranks categories based on the total relevance weight of the matches found.
If an exact match is missing, the LLM uses the keywords and the category context to fill slots with the most adjacent available skills.
The final selection is injected as a pre-formatted LaTeX block (see selected_skills_latex).
Keep category labels consistent with your template’s cvitem headers. If you change a label here, ensure the LaTeX template is updated to match, otherwise compilation will succeed but the formatting may misalign.
Projects (AI payload)¶
Location:
job_hunt/prompts/projects/projects_payload.md
What the LLM reads when selecting which projects to highlight.
Format: name | keywords | description.
- cloudscale | microservices, backend, distributed systems, AWS, Docker
Distributed microservices platform handling 1M+ daily requests.
- codeinsight | AI tooling, code review, developer experience, GitHub
AI-powered code review assistant that reduced review time by 40%.
- datastream | Kafka, Spark, real-time analytics, stream processing
Real-time analytics pipeline ingesting 500K+ events per minute.
- devtrack | dashboards, developer productivity, analytics
Internal productivity dashboard used by 200+ developers.
Use keywords that match the vocabulary in your target job postings.
Project name → LaTeX mapping¶
Location:
job_hunt/prompts/projects/projects_name_to_latex.md
Maps the plain-text names (used by the LLM) to their LaTeX command names
(used in the templates). Every key must exist in projects_payload.md
and every value must exist in both variants_cv.tex and
variants_cl.tex.
{
"cloudscale": "\\cloudscale",
"codeinsight": "\\codeinsight",
"datastream": "\\datastream",
"devtrack": "\\devtrack"
}
Background skills¶
Location:
job_hunt/prompts/background/background_payload.md
The LLM picks three skills from this list to populate the
your_background field in the cover letter. Use plain, lowercase phrases.
Available backgrounds:
- distributed systems
- backend development
- API design
- cloud infrastructure
- microservices architecture
- data engineering
- system design
- DevOps practices
- performance optimization
- database systems
- software architecture
- full-stack development
Sentence style rules¶
Location:
job_hunt/prompts/sentence/sentence_prompt.md
Controls how the LLM writes the tailored opening sentence of your cover
letter (--cl / --tailor_sentence). Adjust:
Tone rules — formal vs. conversational, sentence length, forbidden clichés (
innovative solutions,passionate about, etc.)Structure rules — what the sentence must reference: company challenge, role scope, your motivation.
Do not rename the output schema fields — only edit the instruction text around them.