An evidence-based Codex skill for managing a job search from candidate profiling through interview preparation.
The skill uses one entry point and loads only the reference module needed for the current task. It can:
- build a verified candidate profile from CVs, publications, portfolios, and public sources;
- discover and screen current openings;
- map job-description requirements to candidate evidence;
- improve and tailor academic CVs and industry resumes;
- track opportunity-specific application artifacts;
- prepare JD-grounded answers and detailed CV or project defenses.
skills/job-search-pipeline/
├── SKILL.md
├── agents/
│ └── openai.yaml
└── references/
├── application-pipeline.md
├── candidate-profile.md
├── cv-improvement.md
├── interview-preparation.md
├── jd-alignment.md
└── job-discovery.md
Ask Codex to install the skill from this repository:
Install the job-search-pipeline skill from
https://github.com/Bowens1998/job-search-pipeline/tree/main/skills/job-search-pipeline
Alternatively, copy skills/job-search-pipeline into $CODEX_HOME/skills/ and restart Codex.
Invoke the skill directly:
Use $job-search-pipeline to review my CV and build a verified candidate profile.
Use $job-search-pipeline to find current roles that match my profile and constraints.
Use $job-search-pipeline to tailor my CV to this job description and prepare interview deep dives.
- Keep one verified source of truth for candidate claims.
- Separate verified facts, candidate-stated information, and inference.
- Never fabricate qualifications, metrics, responsibilities, or outcomes.
- Preserve a master CV and create separate opportunity-specific versions.
- Verify live openings with dated sources.
- Require user approval before external submission or messaging.
MIT