feat: rebuild evidence-first application workflow

AGENTS.md

@@ -16,15 +16,19 @@
 └── 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    # 8-part critique system
+│   ├── critique_framework.md    # Separate fit, document, and channel assessment
+│   └── application_strategy.md  # Targeting and cohort strategy
 ├── templates/                   # LaTeX .cls + .tex templates
-├── helpers/                     # char_count.py
+├── 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
@@ -53,6 +57,16 @@ You write as the strategist but critique as the reader.
 - 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.
+
 ---
 
 ## User Focus Directives
@@ -61,7 +75,7 @@ You write as the strategist but critique as the reader.
 - **"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
-- **"Make B a 2L"** — override default variant
+- **"Keep B concise"** — shorten without deleting material evidence
 
 If no directives, use bundle's Priority Matrix defaults.
 
@@ -133,7 +147,7 @@ All templates load `mhchem` (`\usepackage[version=4]{mhchem}`). Use these conven
 
 **CRITICAL:** `~` in LaTeX is a non-breaking space, NOT a tilde. Use `$\sim$` for "approximately."
 
-For char counting: `\ce{TiO2}` → 4 rendered chars, `$\beta$` → 1 rendered char.
+Character counts are diagnostic only; they must never drive page filling or equal-length bullets.
 
 ---
 
@@ -143,10 +157,12 @@ _Update this section when starting/finishing a JD._
 
 | Session | Status | Next Command |
 |---------|--------|-------------|
-| NATO JWC — Staff Officer (2030 Digitalisation – AI Engineer), Stavanger | **SUBMITTED 2026-07-10 via NTAP.** Compact 2-page resume, 1-page cover letter and portal responses submitted. Strong production ML/data reliability, limited domain-grounded LLM-agent configuration, German officer service and German nationality. Known gaps: 3+ years LLM ownership, fine-tuning/agents/hybrid search, Azure DS cert and current clearance. | Done — await response |
+| 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 | **PASSED HIRING ASSESSMENT 2026-06-20 — Recruiting reviewing candidacy for next steps** (applied 2026-06-15, 85.5/100; cleared recruiter screen + assessment). Pass valid 24 months for future Google reqs. Possible additional role-knowledge OA may follow. Next: await recruiter outreach for interview scheduling; clarify L4/L5 + comp clears 180k+ when recruiter re-engages | Await recruiter next-step; prep for recruiter/tech screen |
-| BIS — Senior Data & Analytics Engineer, Artificial Intelligence (Basel; 3-year fixed term) | **SENT 2026-07-10.** 2-page resume + 1-page cover letter; critique 80.5/100. Known ceiling: formal LLM evaluation, direct LLM ownership and banking domain; portal answers framed the LLM scope accurately. | Done — await response |
+| 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 |