dennisthiessenandClaude Opus 5
0eda29327a
The user asked whether Citadel has a hybrid model. The JD is silent: grepping the verbatim posting for hybrid, remote, onsite, in-office and days per week returns zero matches. Phase 0 scored practical constraints 5/5 on an unexamined assumption that Zurich was workable. Withdrawn. Ken Griffin is on record that Citadel returned to the office five days a week, early and deliberately, and calls it his most important leadership decision of the past seven years - framed as core apprenticeship culture rather than a policy setting. The only contrary evidence is an anonymous 2022 Fishbowl post about Operations claiming three days minimum: four years stale, wrong division, contradicted by the founder on record. No official Citadel Securities Zurich policy statement could be found. If five-day onsite holds for Zurich, it means roughly 2 to 2.5 hours of commuting per day from Bern, or relocating - which breaks both the Bern-based, 2-3 day hybrid bar in user_comp_bar and the "keep a Swiss home base" constraint in user_international_mobility. Practical constraints 5/5 -> 2/5 (language and authorization stay clean: English working language, EU citizen, Swiss B permit). Evidence Fit 74 -> 71, still Adjacent but mid-band rather than a point below Core. More consequential than the number: critique_framework.md treats an unresolved location or relocation constraint as a NO-GO trigger, so the qualifications gate passes while the practical gate does not. Phase 2 is blocked pending an answer. This has to be asked, not researched - the same class of question as the SBB Anforderungsniveau K band. Recording the sequencing explicitly, because SBB was submitted with its equivalent question still open and that question is now a live screening topic instead of a settled fact. Repeating it here should be a deliberate choice, not an oversight. The Phase 1 bullet plan is written and unaffected: 11 recommended, 14 with options, budget PASS. Two items still open - the Vizrt VZ-1 C++/distributed bullet the user previously skipped on Snowflake, and adding a Projects section for PP-1. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01MHtzyTKBcg6BWhD5qFegtK
Evidence-first resume kit
This repository turns verified career evidence into role-specific LaTeX resumes and, when useful, cover letters. It is designed to prevent a common failure mode of AI-assisted applications: making a document sound closer to the job description by silently overstating skills, scope, titles, or outcomes.
The workflow separates three questions that should never be confused:
- Evidence Fit: does the candidate actually meet the role, including hard gates?
- Document Quality: does the resume communicate the supported evidence clearly?
- Channel Strength: is the application cold, referred, or supported by a warm contact?
A polished resume cannot repair a failed qualification gate. A strong fit can still be hidden by a weak document. The system records both.
Source hierarchy
source documents
-> structured extractions
-> canonical claims registry
-> experience records and role bundles
-> session plan
-> generated resume / optional cover letter
resume_builder/canonical/claims.json is the highest-authority career source. Generated files under output/ are never treated as evidence. historical_outputs.json records whether an older package is safe to consult, must be revalidated, or must not be reused.
Default application strategy
- Target Staff/Senior Data Engineering first.
- Use ML Platform/MLOps, data platform, analytics, and semiconductor profiles only where direct evidence covers the actual requirements.
- Treat direct LLM engineering, formal model evaluation, Terraform-heavy SRE, and similar missing required experience as gates rather than keyword opportunities.
- Build application cohorts with roughly 70% core, 20% adjacent, and 10% deliberate stretch roles.
- Add a warm-channel action for core applications.
The default document is a two-page International Tech resume for US-tech/FAANG-style roles in Europe. A Swiss/DACH policy overlay is available for employers that expect local conventions. Cover letters are conditional, not automatic.
Workflow
Add evidence
- Put employment records, project material, papers, or notes under
knowledge_base/. - Run
setup-extractto create a source-grounded extraction. - Review it, then run
setup-build-kbto update canonical claims, experience files, bundles, and support data.
Apply to a role
- Run
make-resumewith the real JD. - Review the requirement table and fit gate before approving content generation.
- Generate and validate the LaTeX resume.
- Run
make-clonly when the session records a justifiedYESdecision. - Run
critiquefor separate Evidence Fit, Document Quality, and Channel Strength findings. - Run
edit-resumefor approved repairs.
The skills live in .agents/skills/. Each application receives a session file under output/<Role>/ that preserves the JD, fit decision, claim IDs, content plan, validation results, and application status.
Validation
Validate the knowledge system:
python resume_builder/helpers/validate_resume_system.py
Validate a generated document:
python resume_builder/helpers/validate_resume_system.py --document output/Role/resume.tex
Track the active 7/2/1 cohort:
python resume_builder/helpers/cohort_tracker.py summary
Character counts are available only as readability diagnostics. There are no fixed character bands, equal-length bullet rules, or page-fill quotas.
Output and prerequisites
The system writes .tex source only. Compile locally with a LaTeX distribution such as MiKTeX, TeX Live, or MacTeX. Generated resumes should also be checked through PDF rendering and text extraction before submission.
See DOCS.md for the architecture and policy reference.
License
MIT; see LICENSE.