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dennisthiessenandClaude Opus 5 afdef7eb94 refactor: shared agent workflows (F01) and one application registry (F02)

Checkpoint for the 2026-09-11 project review remediation. Work by a previous
agent that ran out of context; committed unchanged as a rollback point before
the remaining findings land on top of it.

F01 — the two agent directories had drifted into different processes
- Six shared workflows under `resume_builder/reference/workflows/`; both
  `.agents/skills/` and `.claude/skills/` are now thin entrypoints that route
  to the same file instead of carrying full copies.
- The `.claude` copies were the stale side: fixed bullet line variants and
  character budgets that the newer process had already dropped. Removing them
  is the point of the change, not collateral.
- Parity/link regression test added; corrected the top-level file map, which
  pointed at a directory that does not exist.

F02 — application status was stored in four places and disagreed
- New registry `job_scout/state/applications.json` (26 records) with
  `application_records.py` (schema, validation, transactional write) and
  `application_tracker.py` (add/update, no quota).
- AGENTS.md and CLAUDE.md no longer keep their own status tables; both point
  at `current_applications.md`, generated from the registry.
- Interview-reached is now independent of outcome, so a withdrawal after an
  interview can record both facts. The old tables are preserved verbatim in
  `job_scout/state/history/application_status_before_2026-09-11.json`.

Verification: `python -m unittest discover -s tests -v` — 18/18 pass.
Spot-checked that the detailed SBB and Kdo Cy notes survived the migration
into the registry rather than being flattened.

Known unresolved, deliberately not invented (see FIX_PROGRESS.md):
Aker BP's application date and its Adjacent-despite-79 classification.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qej5SBvhcbGXHwLqNWiskM

2026-09-11 19:23:13 +02:00

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Build or Update the Knowledge Base

Authority Model

The pipeline is:

source documents -> extractions -> canonical claims -> experience records/bundles -> generated applications

Generated applications never flow backward into the KB.

Read resume_builder/canonical/claims.json, config.md, and all relevant extractions before changing normalized sources. Preserve raw source documents. A verified correction must update canonical claims first and then every dependent normalized file.

Canonical Claim Record

For each employment item or achievement, record:

stable ID;
employer, title, dates and location;
factual scope;
individual vs shared ownership;
allowed verbs;
forbidden overstatements;
metric/result and verification status;
evidence source;
last verified date.

When ownership is ambiguous, use contributing/shared scope and ask the user. Do not default to full ownership.

Experience Files

Experience files explain facts and context. They may contain example phrasings, but those examples cannot override canonical scope and should not be optimized to fixed line counts.

Every achievement section must include canonical ID, source, ownership scope, status, verified result/metric state, relevant skills and role relevance.

Skills Taxonomy

Use only these evidence levels:

Production — current.
Production — historical.
Hands-on — current.
Project / proof of concept.
Certification / coursework.
Unverified / never used.

Do not assign Expert/Proficient/Familiar labels. Add a skill to canonical claims before it can appear in a generated document.

Role Bundles

Each bundle must contain:

Defensible positioning.
Good-fit roles and hard-gate cautions.
Achievement priorities.
Safe reframing rules.
Evidence-backed skills guidance.
Conditional cover-letter guidance.

Bundles may rank evidence; they may not broaden it. Title-defining gaps must be stated explicitly.

Significance Context

Keep company/industry context separate from candidate impact. Mark external claims for re-verification at application time. Never attach generic scale, economics, customers or market trends to the candidate.

Correction Propagation

After any correction, search canonical claims, config, extractions, experience files, bundles, support files, templates and active drafts. Historical submitted outputs remain unchanged but update historical_outputs.json when they become unsafe for reuse.

Validation

Run:

python resume_builder/helpers/validate_resume_system.py

Then review the diff for dates, titles, ownership, metrics and skill evidence. Present the changed claim records and affected downstream files to the user for confirmation.

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