DB-cleanup/README-START-HERE.md

Gart K&R Database - Handoff (read this first)

Written 2026-09-02. This folder is a self-contained bundle. Everything the next AI needs to continue is inside it, and all script paths are relative, so the folder can be moved or zipped and still run.

Read order: (1) this file, (2) merge-output/sofia-worklist.md (the human's manual task list).

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Folder layout

Gart-KR-handoff/
  README-START-HERE.md              <- this file
  source-checker-agent.md           <- the read-only reviewer agent (install in .claude/agents/)
  attacks-export-Gart-website.json  <- SOURCE: the live DB export (read-only)
  KR-reports_analysis_Sofi.xlsx     <- SOURCE: the old article spreadsheet (read-only)
  merge-output/
    sources/                        <- THE DELIVERABLE: 364 .txt dossiers (build_cases writes here)
    build_cases.py                  <- rebuilds all 364 .txt files
    verify_all.py                   <- deterministic audit (must say PASS)
    survey_summaries.py             <- lists which cases still have short summaries
    build_overrides_batch1..7.py    <- the summary rewrites, one script per batch
    dump_cell.py                    <- helper: prints a spreadsheet cell line-by-line
    summary-overrides.json          <- the improved summaries (build input)
    sheet-trim-decisions.json       <- article furniture cuts (build input)
    sourced-articles.json           <- fetched-article store (build input)
    sofia-worklist.md               <- the human's manual to-do list
    (other .py and .json files are finished-phase artifacts, not needed to continue)

Scripts live in merge-output/ and must be run from there (they find the two source files in the parent folder automatically). Always call them with the full path, for example: python "/Gart-KR-handoff/merge-output/build_cases.py" --all

Requirements to run this:

• Python 3 with the openpyxl package (pip install openpyxl) - build_cases.py reads the .xlsx.
• The review step uses a read-only fact-checking sub-agent. Its definition is included here as source-checker-agent.md (bundle root). In Claude Code, drop it into your project's .claude/agents/ folder so you can invoke it; otherwise any capable read-only checker works - just feed it the source-checker prompt (further down this doc) plus the batch's file list.

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What this project is

Gart's K&R attack database lists 364 real kidnap/robbery/extortion incidents against cryptocurrency holders. For each case we merged the structured DB record with any saved news article, and produce one readable .txt dossier per case. There is no app, no build system, no tests - just Python scripts that regenerate the .txt files, plus Markdown notes.

Hard rules (do not break these)

1. Never edit the live database. attacks-export-Gart-website.json and the .xlsx are READ-ONLY. Any DB correction goes to sofia-worklist.md for Sofia to apply herself.
2. Never fabricate. Every statement must trace to that case's own DB record or its article text. If a source does not say it, do not write it. Record-only cases stay short - do not pad them.
3. Do not translate articles into the archive. Non-English article text is stored verbatim. You MAY read a foreign-language article to write an English summary (that is derived facts, not a stored translation), but never write a translation into a stored file.
4. Work in descending ID order (nothing gets skipped).
5. Every record-vs-article contradiction is a note for Sofia - log it, do not "resolve" it by guessing which side is right.

Environment

• Windows / PowerShell, with a Bash tool available (Git Bash).
• In the Bash tool, a "cd" inside a compound command triggers a permission prompt - always use full paths instead.
• Any Python script that prints non-ASCII must wrap stdout, or it crashes on Windows: import sys, io sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding="utf-8", errors="replace") Put that inside main() if another script imports the file.

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The deliverable, and what still needs the human

Two different kinds of change came out of this work. They are NOT the same:

1. The improved SUMMARIES are already baked into the .txt files. build_cases.py renders each rewritten summary into its dossier under the banner "AI SUMMARY [revised on review ...]". So if Sofia uploads the .txt files as the DB's dossier source, the summaries are upgraded. There is no separate "apply-list" to work through for summaries. summary-overrides.json is just the build INPUT that injects them; it is not a manual chore.

2. The DB FIELD / FLAG corrections in sofia-worklist.md are NOT in the .txt files. The DATABASE RECORD block in each dossier is printed verbatim from the live DB, so it still shows the old, wrong field values (for example case 353 still says "100 million rubles", case 219 still says "beaten with a stick"). Uploading the .txt does NOT fix those. They are advisory notes for Sofia to apply on the DB side if and when she wants. She said she will do these last.

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What is already FINISHED

• Matching: all 364 records matched to their spreadsheet rows / fetched sources.
• Article merge: spreadsheet and web-fetched articles are in the dossiers.
• Article trimming: site furniture removed from fetched and spreadsheet articles; every kept line is a verbatim line of the source; provenance hashes preserved. Reviewed twice.
• Source-coverage reconciliation: 344 of 364 cases have a usable source; 20 have none (all listed on the worklist). No case silently lost its last source.
• verify_all.py PASSES (896 checks). Confirmed from this bundle's new location.

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The task in progress: summary enrichment

Goal: bring the short/weak bulk-import summaries up to the standard of the newest cases (447-462), which have six labelled categories and run roughly 970-2100 characters: Victims / Attackers / Attack Method / Violence Used / Crypto Demanded/Stolen / Status

A survey (survey_summaries.py) found 256 of 364 cases under the bar (under 400 chars or fewer than 4 categories). These are the targets, worked in descending ID order.

How it works

• Rewrites live in summary-overrides.json, keyed by DB id (string).
• build_cases.py loads it and renders the rewrite in place of the old bulk summary.
• The live DB export is never touched.

Method, per case

• Read the whole dossier: the DATABASE RECORD block AND every ARTICLE / FETCHED ARTICLE section (any language).
• Write the six categories from ONLY what the record + that case's articles support. No repeated facts across categories. Keep the source's own hedging ("allegedly", "police said", "he says").
• Record-only or wrong-source cases (dead/blocked/thin link): restructure the record's description + notes + flags into the six categories, faithfully, and stay short. Do not invent.
• Round-up articles (one article, several incidents): use ONLY the passage about THIS case; drop the other incidents and any trend-commentary tail.
• Foiled / "dodged" attacks with no one harmed: "Violence Used: None - the attempt was foiled."

Workflow per batch (about 10 cases)

1. Write build_overrides_batchN.py (copy an existing one; it does existing.update(B) then writes summary-overrides.json; escape non-ASCII with \uXXXX). Run it.
2. Run build_cases.py --all, then verify_all.py (must say PASS).
3. Run the source-checker sub-agent (read-only; tell it NOT to fetch) to fact-check the batch's summaries against each file's own record + article. This is Sofia's explicit requirement.
4. Fix every fair flag in the batch script, rebuild, verify. The batch is then locked.
5. Add any DB field/source problems you find to sofia-worklist.md.

The source-checker prompt that works

"Read-only fact-check. Do NOT fetch. For each file, verify every claim in the revised summary (under the 'revised on review' banner) is supported by the DATABASE RECORD block and/or the embedded article text in the SAME file. Flag FABRICATED / CONTRADICTED / OVERSTATED (note: source-matching hedges like 'allegedly' are correct, not flags). Tell it about round-up files, foiled plots, and any known wrong-source case so it does not over-flag."

The pitfalls the reviewer keeps catching (avoid these up front)

1. Dropped hedges - keep "allegedly / he believes / police said"; do not state a claim as fact.
2. Inferred negatives - do not write "no arrests reported" when the source is just silent on it.
3. Unsupported cross-links - do not tie a case to another case unless THIS file says so.
4. Added specifics not in the file - no invented brand ("Toyota" when it says only "Vigo"), residency, or family composition ("two parents" when only "the mother" is mentioned).
5. Number / currency / date math - get units exact; when the DB date and the article date disagree, say "late March" and log the conflict rather than silently picking one.
6. Mis-attributed timestamps - a time in the article belongs to a specific moment; do not move it.
7. Round-up / tail exclusion - use only this case's passage (the reviewer expects this).
8. Follow the article over a wrong DB field, and log the conflict on the worklist. Exception: a record-only / wrong-source case has no article - write from the record and say so.
9. Naming - only name a person the linked source names. If the source withholds the victim's name but the DB carries one, describe the victim generically in the summary body.

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Progress

Done and reviewer-verified: batches 1-7, 70 of 256 cases. IDs completed: B1: 372,371,370,369,368,367,365,364,362,353 B2: 350,349,340,334,323,322,321,317,315,312 B3: 309,308,307,304,303,301,299,298,297,296 B4: 293,292,290,288,285,279,273,272,271,270 B5: 266,263,256,253,252,249,248,247,246,245 B6: 244,243,242,240,238,237,236,235,234,233 B7: 232,231,230,229,228,224,222,221,219,218

summary-overrides.json holds 70 entries. verify_all.py PASSES.

Remaining: continue descending from ID 217 (217,216,215,214,213,212,211,210,208,207 ...) down to case 1 - about 186 short cases, roughly 19 more batches. Get the exact remaining list with: python ".../merge-output/survey_summaries.py" and take the ids flagged SHORT / unstructured, descending.

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Quick-start checklist for the next AI

1. Read this file and merge-output/sofia-worklist.md.
2. Confirm the bundle is healthy: python ".../merge-output/verify_all.py" (should say PASS) summary-overrides.json should have 70 entries.
3. Pick the next ~10 short cases descending from ID 217 (use survey_summaries.py). Read each dossier in full. Write build_overrides_batch8.py (copy batch 7's structure). Run it, then build_cases.py --all, then verify_all.py.
4. Run the source-checker agent on the batch (read-only, no fetch). Apply fair flags; rebuild; verify. Then the batch is locked.
5. Repeat down to case 1.
6. Keep adding DB field/source problems to sofia-worklist.md. Never edit the DB.
7. When all summaries are done, the deliverables are: the sources/*.txt (already carry the improved summaries) and sofia-worklist.md (Sofia's manual DB fixes, done last on her side).