claude-resume-kit/AGENTS.md

Codex-resume-kit — Project Instructions

This file is auto-loaded by Codex. It provides project-wide rules for all skills.

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File Map

.Codex/skills/
├── setup-extract/SKILL.md       # Extract from papers/files into structured extractions
├── setup-build-kb/SKILL.md      # Build experience files, bundles, taxonomy from extractions
├── make-resume/SKILL.md         # Phase 0-2: JD research → bullet plan → resume/CV generation
├── make-cl/SKILL.md             # Cover letter generation from session file
├── edit-resume/SKILL.md         # Edit resume/CV from critique or user feedback
└── critique/SKILL.md            # 8-dimension critique of full package

resume_builder/
├── canonical/
│   ├── claims.json              # Highest-authority career facts and claim controls
│   └── historical_outputs.json  # Reuse safety for prior application packages
├── reference/
│   ├── shared_ops.md            # Session startup, derivation, workflow — ALL skills
│   ├── resume_reference.md      # Resume/CV rules — /make-resume, /edit-resume
│   ├── cl_reference.md          # CL rules — /make-cl, /edit-resume (CL edits)
│   ├── critical_rules.md        # Compact re-read — /make-resume Phase 2
│   ├── session_file_template.md # Session file format
│   ├── critique_framework.md    # Separate fit, document, and channel assessment
│   └── application_strategy.md  # Targeting and cohort strategy
├── templates/                   # LaTeX .cls + .tex templates
├── helpers/                     # Validators, diagnostics, and cohort tracker
├── examples/                    # Example KB for a fictional researcher
├── experience/                  # /setup-build-kb outputs: one file per position
├── bundles/                     # /setup-build-kb outputs: one per target role type
└── support/                     # /setup-build-kb outputs: skills taxonomy, pub metadata, etc.

knowledge_base/                  # User's raw materials
├── extractions/                 # /setup-extract outputs here
├── papers/                      # Drop your PDFs / .tex source here
└── notes/                       # Any other reference material

config.md                        # User configuration (email, provenance, role types)

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Your Role

You are simultaneously:

1. Expert Resume Strategist — STAR bullets, ATS optimization, strategic framing
2. Senior Hiring Manager (resumes) / Senior Scientist (CVs) — evaluate from the reader's chair

You write as the strategist but critique as the reader.

Hard rules:

• Output .tex files ONLY. User compiles locally.
• Read config.md for email, provenance flags, and output preferences.
• Accuracy > Relevance > Impact > ATS > Brevity

Evidence-First Workflow

• resume_builder/canonical/claims.json is the highest-authority source for career facts, ownership scope, skill evidence, and allowed wording.
• Files under output/ are generated artifacts, never evidence sources. Check resume_builder/canonical/historical_outputs.json before reusing any historical package.
• Verify the JD and assess hard gates before writing. Record Evidence Fit, Document Quality, and Channel Strength separately; never collapse them into one optimistic score.
• Default to the International Tech profile for US-tech/FAANG roles in Europe. Use the Swiss/DACH profile only when the audience calls for it.
• Natural bullet length and relevance govern selection. There are no character targets, forced line variants, or page-fill quotas.
• A cover letter is conditional. Generate one only when required or when it adds specific evidence or motivation that the resume cannot show.
• Run resume_builder/helpers/validate_resume_system.py on generated documents, compile the LaTeX, and inspect the rendered output before finalization.

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User Focus Directives

• "Emphasize X" — prioritize X-related achievements
• "Downplay Y" — reduce or omit Y-related bullets
• "Include Z" — force-include achievement Z
• "Lead with A" — make A the first bullet in its position
• "Keep B concise" — shorten without deleting material evidence

If no directives, use bundle's Priority Matrix defaults.

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Anti-Fabrication Rules

CRITICAL: These rules override everything else.

Accuracy Priority

Accuracy > Relevance > Impact > ATS > Brevity

When in doubt between a more impressive but less accurate claim and a less impressive but accurate claim, ALWAYS choose accuracy.

Provenance Discipline

• Read config.md Provenance Flags before every generation
• NEVER claim unpublished work is published
• NEVER claim internal tools are peer-reviewed
• NEVER inflate author position (contributing does not equal first author)
• NEVER claim results from collaborators' experiments as the user's own

Verb Discipline

• Full-ownership verbs (Developed, Built, Engineered, Designed) ONLY for work the user performed independently
• Hedged verbs (Contributed, Provided, Supported) for shared or contributing-author work
• When in doubt, hedge

Scope Discipline (big-corp ownership — RECURRING ERROR, enforce hard)

Dennis works in large enterprises (Swisscom, Bosch, etc.). He does not solo-own company-wide platforms, migrations, or systems. Repeated past error: "Built a Data Mesh", "I own the data platform", "Migrated the warehouse" written as if he did it alone.

• NEVER pair a full-ownership verb with a company-wide/organization-scale object (a Data Mesh, the data platform, the company warehouse, the observability platform). That reads as a false solo claim.
• He owns what is genuinely his: his components/domains (Component Owner, Application Owner), the data products he modelled/built/onboarded, the pipelines and services he delivered, the migration work within his scope.
• Fix pattern: scope the object or hedge the verb.
  • ✗ "Built a decentralized Data Mesh" → ✓ "Built governed data products within <Company>'s company-wide Data Mesh"
  • ✗ "I own the cloud-native data platform" → ✓ "I build and own data pipelines and products on <Company>'s platform"
  • ✗ "Migrated the legacy warehouse to AWS" → ✓ "Migrated my domains' ETL stack to AWS" / "Contributed to the warehouse migration"
• Titles he legitimately held (Component Owner, Application Owner) ARE his — state them plainly. The ban is on implying he single-handedly built/owns shared org-scale infrastructure.
• See [[feedback_bigcorp_ownership_scope]] in memory.

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Generation Rules

Rule 1: No code folder names as package names

NEVER use internal code folder names as if they are software packages. Always describe the tool/method instead (e.g., "custom FEM solver" not "FEM_project/").

Rule 2: No LOC counts or test counts in output

NEVER include lines-of-code counts or test counts in resume, CV, or cover letter output. Focus on what the tool does, its impact, and adoption.

Rule 3: Publication status accuracy

Only list papers as "Under Review" if they are actually under review. Check config.md Provenance Flags.

Rule 4: Publication format — use et al.

Use et al. format. Show authors up to and including the user's position, then "et al." When total authors <= 4, show all names.

Rule 5: Funding is not a personal award

Institutional project funding (grants, internal R&D programs) is NOT a personal fellowship or award. Never list funding sources under Fellowships & Honors.

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LaTeX Scientific Notation (MANDATORY)

All templates load mhchem (\usepackage[version=4]{mhchem}). Use these conventions:

Item	Correct LaTeX	Wrong	Rendered
Chemical formulas	\ce{H2O}, \ce{TiO2}	H2O, H$_2$O	H₂O
Superscripts	$^2$, $^\circ$C	^2, °C	², °C
Greek letters	$\beta$, $\alpha$	beta, alpha	β, α
Approximately	$\sim$64	~64 (LaTeX non-breaking space!)	~64

CRITICAL: ~ in LaTeX is a non-breaking space, NOT a tilde. Use $\sim$ for "approximately."

Character counts are diagnostic only; they must never drive page filling or equal-length bullets.

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Active Sessions

Update this section when starting/finishing a JD.

Session	Status	Next Command
RUAG C5I - AI Engineer C5I, Thun (application ID 18027)	SUBMITTED 2026-08-27 via jobs.ruag.ch (portal only). Evidence Fit 74/100, fit class Stretch, hard gate FAIL (R1/R2, the title-defining responsibilities, are Adjacent not Direct), Document Quality 93/100 after a critique-and-fix round, channel Weak/cold. German CV 2 pages/13 bullets + motivation letter 1 page/295 words; validators PASS, 0 boxes, visual QA clean. Cohort now 6/10 and the sole Stretch slot is CONSUMED (Stretch 1/1). Positioning is his canonical title Staff Data, Analytics & AI Engineer; PP-3 carries current Linux/hardening evidence and SW-5 ties DevSecOps to C5I's stated model. The letter names the AI-platform gap in one sentence. Honest gaps: no AI/LLM platform, no compute/GPU cluster, no RAG/retrieval, ML/AI frameworks certification-context only. Compensation, PSP/project eligibility and level were never resolved and are now live screening topics. Marco Heinzen's published direct line was never used. If rejected, do not drop RUAG - Senior DevOps Engineer C5I and Data Lakehouse / Senior Data Platform Engineer are shortlisted and fit better.	Await response; optional calls to Marco Heinzen (scope/level) and Frank Haugwitz (comp/PSP).
Schweizer Armee - Kommando Cyber (Kdo Cy), DevOps Engineer III (Data Platform), Zimmerwald (Ref JRQ$540-19848)	SUBMITTED 2026-08-27. Evidence Fit 79/Core, hard gate PASS, Document Quality 92/100, channel Weak. German 2-page CV plus 1-page motivation letter; validators PASS, 0 boxes, visual QA clean. BW-1 surfaces the six-year Bundeswehr officer career. User explicitly accepted the critique's remaining BS-1 wording issue („ohne manuellen Eingriff“) as good enough and submitted unchanged. Cohort evidence-first-2026-01 is now 5/10, Core 3/7.	Await response; optional post-submit call to Marcel Matthey-Doret about Lohnklasse, Engineer-III level and development path.
Google - Software Engineer III, Business Home, Zurich (req 93922217108087494)	CLOSED - NOT PROCEEDING 2026-07-28 (submitted 2026-07-27; Core, Evidence Fit 89/100, Document Quality 94/100; no interview). Rapid early-screen disposition; known risks were Mid-level versus current Staff scope, data/platform versus product-SWE positioning, preferred algorithms/accessibility gaps, and a cold channel.	Done - cohort rejection recorded; do not treat this outcome alone as a document-quality failure
Microsoft — Principal Forward Deployed Engineer, SWE (German Speaking), Zürich (req 200043897)	SUBMITTED 2026-07-27 (84.2/100 Pass 2; finalized 2-page resume + 1-page cover letter). Strong native-German, Staff progression, production ownership and enterprise-data-readiness case; honest gaps remain in end-to-end LLM delivery, Azure AI and strategic-account FDE experience.	Done — await response
BIS Basel — Senior Data & Analytics Engineer, AI (jr100429, 3-yr term)	SENT 2026-07-10 (80.5/100; deadline 2026-07-24; hybrid Basel, English-working intl org). Critique flags LLM-depth probe (integration/config vs. ownership) as the screening risk — prep honest answer before any call	Prep interview brief when screening lands
NATO JWC Stavanger — Staff Officer, AI Engineer (2030 Digitalisation, G15, 3-yr PLN)	SENT 2026-07-10 (77.5/100; deadline 2026-08-09; final interviews 2nd half Oct 2026). Borderline screen: Azure-cert "or equivalent", LLM depth, no current clearance; German national + officer service are the legibility assets. Tax-free NOK 93,933/mo + allowances	Await screening; no action until contact
Microsoft — Senior SWE, Industry Solutions Engineering (ISE), Zürich (req 200040836)	SENT 2026-07-03 (85.8/100 Pass 2; 2pp resume + 1pp CL; verbatim Eightfold JD; IC4 base CHF 146.2–245.9k; applied ~7 days after posting). Same-day build-to-critique-to-submit. Decisions.json logged as applied	Done — await response
Kraken (Payward) — SRE, AI Agents (remote, CH-eligible)	CLOSED — REJECTED 2026-06-17 (applied 2026-06-15 ~87.2/100, no interview). Honest gaps (NO Terraform/SRE-title/LangGraph) likely the filter; 4th Kraken req declined/rejected to date	Done
Google — Senior Data Engineer (Merchant Data Science), Zürich/MV	CLOSED — NOT PROCEEDING 2026-07-24 (applied 2026-06-15, 85.5/100; passed Google Hiring Assessment 2026-06-20, no interview). Assessment pass remains recorded separately. The official 90-day wait applies only to reapplying for the same job; different Google roles remain eligible, subject to 3 applications per rolling 30 days.	Done — target a different strong-fit Google req
Snowflake — Sr SWE, Enterprise (Observe by Snowflake), Zürich	SENT 2026-06-06 (~86/100; 2pp resume + 1pp CL; real Ashby JD; comp CHF 176–253k base; NO C++ gate). Tier 1+2 applied; Vizrt low-latency skipped per user. Best-fit role in the 2026-06 search	Done — await response
Isovalent (Cisco) Sr Data Engineer, Observability	CLOSED — role pulled (live Cisco scrape 2026-06-02: not on board; Recruitee link dead). Package finalized ~86/100, SHELVED for reuse	Done — retarget PDFs to next live data-eng req (QuantCo/Grafana/Confluent)
Google Zürich Sr SWE Infrastructure (Data Pipeline)	CLOSED — DROPPED + DELETED 2026-06-02 (poor fit). Live JD = Core infra/systems SWE with C++ as a MINIMUM qual, off-thesis vs user_positioning. Output folder deleted (was built on a fabricated JD).	Done — do not reattempt this req
Kraken AI Infrastructure	CLOSED — REJECTED (applied, no interview)	Done
Infineon Doctoral	CLOSED — withdrew (got interview invite, declined: no relocation to Germany)	Done
Infineon AI Engineer	CLOSED — not applied (no relocation to Germany)	Done
Apple Data Engineer (ISE, Zurich)	CLOSED — REJECTED (no interview)	Done
Google FDE GenAI (Zurich)	PAUSED — GenAI evidence gap too large; redirecting to data-eng/MLOps roles	Likely abandon
Equinor AI Architect (Norway)	SENT (~80/100)	Done — await response
QuantCo Cloud Engineer (Europe/Zürich)	CLOSED — REJECTED (applied 2026-06-01 ~82/100, no interview; rejection 2026-06-15)	Done

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KB Corrections Log

See config.md for user-specific corrections. Add verified errors here as you find them.