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NOSOUP74/README.md

Olivia Steele · Technical Delivery (Team)

Hire us for offline Python automation and data cleanup.
I manage scope and final quality. A specialist technical team builds and ships under that bar.

Samples first · fixed-price when scope is clear

Mississippi, USA · English & Spanish · Fixed-price when the job is clear

Pinned for clients (open these first)

  1. python-data-cleanup — folder → clean table
  2. csv-clean-demo — before / after CSV
  3. dump-sense-making — messy dump → inventory
  4. project-gap-board — missing-pieces board
  5. Victor-Memory-Architecture — team R&D (memory ideas + math)
  6. This profile — hire menu

What you can buy (detailed)

Product What you get Open this
Folder → table Messy inbox folder → clean CSV + SQLite + quarantine; crash-safe python-data-cleanup · Release v0.2.1 zip
CSV / Excel cleanup Before/after demos; money formats, dupes, contact normalize csv-clean-demo
Dump sense-making Inventory → classify → known vs unproven brief dump-sense-making
Project gap board Missing-pieces spreadsheet that stops forgotten work project-gap-board
Graded research pack Open sources graded A/B/C + claim tables (dig ≠ proof) research-method-graded-sources
Custom small Python One workflow automated; zip + runbook Quote after samples

Always true on paid work

  • Tools run on your PC (offline-friendly)
  • You keep a zip — no monthly SaaS rent
  • No access to private internal systems
  • Sample-proven before we call it done
  • Package shape documented: CLIENT_PACKAGE_TEMPLATE

Start here (free proof)

  1. csv-clean-demo — open samples/before vs samples/after
  2. python-data-cleanup — run the folder pipeline on included samples
  3. dump-sense-making — read inventory + classified + brief
# folder product demo
cd folder_pipeline
python pipeline.py run --inbox samples/inbox --out samples/out

How we work

You send redacted samples
    → we confirm fields + price + done-means
        → zip + runbook + proof
            → you run it; we fix package defects
Role Who
Public face, scope, quality gate, final say Olivia Steele
Systems / code / experiments (AI-assisted) Technical build team
Client receives Isolated package only

Team R&D (depth — not client installs)

Public research; experimental where noted (dig ≠ proof).

Area Repos
Governed AI memory victor-memory-infrastructure · Victor-Memory-Architecture
Physics / math experiments k-fractal-stability-law · e-lock-fractal- · fold-math-e-lock
Signal notes ligo_o4 analysis
Research honesty method research-method-graded-sources

Private house systems stay private.

Hire / quote

  1. Pick a product repo above
  2. Open issue Quote request with 3–5 redacted samples (or describe the dump)
  3. Or contact via Fiverr / marketplace under Olivia Steele

Not for sale: full private AI house · open-ended “do anything” · scrape farms · secrets.

Pinned Loading

  1. csv-clean-demo csv-clean-demo Public

    Isolated package: CSV/Excel cleanup demos — messy before vs clean after. Olivia Steele, offline samples.

    Python

  2. dump-sense-making dump-sense-making Public

    Isolated package: make sense of a messy file dump — inventory, classify, grade known vs unproven, brief. Olivia Steele method sample.

  3. python-data-cleanup python-data-cleanup Public

    Isolated package: offline Python — messy folder/CSV to a clean table (CSV + SQLite). Olivia Steele client-safe demo.

    Python

  4. NOSOUP74 NOSOUP74 Public

    Olivia Steele — hire for offline Python automation & data cleanup. Team delivery. Public samples + R&D (memory systems, physics).

  5. project-gap-board project-gap-board Public

    Isolated package: project missing-pieces tracker — gap spreadsheet sample. Olivia Steele, offline and simple.

  6. Victor-Memory-Architecture Victor-Memory-Architecture Public

    Team R&D: public architecture for governed agent memory (braids, PhaseLoom, lenses). Research notes, not a client install.

    Python