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# Agent Context
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This file exists so a restarted coding agent can recover quickly in `NTT-learning` without relying on vanished session memory.
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## Identity
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- Project: `NTT-learning`
- Directory: `/Users/oho/GitClone/CodexProjects/NTT-learning`
- GitHub: `https://github.com/saymrwulf/NTT-learning`
- Branch: `master` only. Do not assume `main` .
- Goal: build the best notebook-first tutorial for understanding NTT / iNTT, especially in the Kyber context, with the real emphasis on:
- convolution and negacyclic structure
- direct transform definitions
- butterfly mechanics
- CT vs GS flow
- ordering / bit-reversal / scaling
- Kyber-specific mapping only after the learner sees the mechanics
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Current course shape:
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- `27` canonical notebooks total
- `3` route notebooks:
- `notebooks/START_HERE.ipynb`
- `notebooks/COURSE_BLUEPRINT.ipynb`
- `notebooks/COURSE_COMPLETE.ipynb`
- `24` technical notebooks across `6` bundles:
- `foundations/01_convolution_to_toy_ntt`
- `foundations/02_negative_wrapped_ntt`
- `butterfly_mechanics/03_fast_forward_ct`
- `butterfly_mechanics/04_fast_inverse_gs`
- `kyber_mapping/05_kyber_ntt_and_base_multiplication`
- `professional/06_debugging_ntt_failures`
## Non-Negotiable User Rules
These are not optional style preferences. Future agents should assume these are hard requirements.
- Read this file first on restart.
- Inspect `git status --short --branch` , `git log --oneline -8` , and the repo tree before acting.
- Work autonomously after that. Do not ask the user to re-explain the project state.
- Always commit and push before returning a final answer.
- Never return with a dirty worktree. Final `git status --short` should be empty.
- UX is first-order priority. If the learner can get lost, the UX is wrong.
- The user is strongly visual and struggles when asked to imagine array motion abstractly.
- Abstractions are bad for this teaching goal unless they come after concrete motion and visuals.
- The course should be blunt, graphical, dynamic, and foolproof.
- If one animation or notebook interaction breaks, assume the bug may be systemic across other players and test broadly.
## Core Teaching Judgement
The course must keep these stories separate:
1. the algebraic purpose of the transform
2. the local in-place butterfly dataflow
3. the Kyber-specific implementation conventions
The learner staircase should remain:
1. ordinary polynomial multiplication / convolution
2. cyclic vs negacyclic folding
3. tiny direct NTT / INTT examples
4. butterfly mechanics in isolation
5. forward vs inverse flow side by side
6. ordering / bit-reversal / scaling
7. Kyber parameter reality and base multiplication
8. only then implementation-reading / debugging studios
Do not dump advanced Kyber implementation detail before the learner has seen small arrays move.
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## Current Notebook Contract
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There is one official learner route only.
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The internal cell-role contract still exists:
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- `meta`
- `mandatory`
- `facultative`
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Difficulty still means:
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- `1-3` reserved for mandatory cells
- `4-10` reserved for facultative cells
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Important UX rule:
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- Raw `META` , `MANDATORY` , and `FACULTATIVE` labels must **not** appear as notebook headlines.
- Content headings must be about the content itself.
- Role and pacing information may appear only through subtle chrome such as colored cards / chips / level badges.
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Route notebooks stay pure:
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- markdown only
- no facultative detours
- clear route guidance
- clickable navigation only
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Every canonical notebook must have:
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- a top route-guardrails cell
- a bottom next-notebook handoff cell
- clickable `Previous` , `Next` , and `Restart route` recovery links
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Never make the learner choose the next notebook manually from the file tree.
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## Current Architecture
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Source-of-truth files:
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- `tools/render_notebooks.py`
- notebook generator
- route guardrails / handoff cells
- notebook chrome
- learner-facing header styling
- `ntt_learning/course.py`
- course constants
- route sequence
- bundle definitions
- `ntt_learning/toy_ntt.py`
- inspectable math helpers
- toy NTT / INTT
- CT / GS traces
- pairings and stage helpers
- `ntt_learning/visuals.py`
- interactive players
- plots
- rendering behavior
- `scripts/app.sh`
- Jupyter lifecycle source of truth
- `tests/`
- contract
- execution
- repo ops
- visual UX
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Do not hand-edit notebook structure when the change belongs in the generator. Change `tools/render_notebooks.py` , then regenerate canonical notebooks.
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## Current Rendering / Animation Rules
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This section matters because several UX regressions already happened here.
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### Stable rules
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- `schoolbook_diagonal_player(...)` is HTML-board based, not SVG.
- `wraparound_comparison_player(...)` is HTML-board based, not SVG.
- The wraparound player was explicitly rewritten because the SVG version jittered and collided.
- `direct_ntt_player(...)` and `butterfly_story_player(...)` still use SVG, but:
- they must render inside horizontal-scroll frames
- their SVG canvases must not shrink to fit the viewport
- they must use fixed canvas widths with `max-width:none` / `min-width`
- Player captions should have a fixed minimum height to reduce layout shift.
### Practical lesson
Dense explanatory text inside shrinking SVG is a bad idea here.
If a player shows:
- text collisions
- jitter between frames
- section labels jumping vertically
- numbers painting over other numbers
then first suspect:
- shrinking SVG layout
- variable-height captions
- too many text bands inside the same visual corridor
### Regression discipline
When fixing one player:
- test the other players too
- extend `tests/test_visuals.py`
- test the failure mode itself, not just “widget exists”
## Current Visual / UX Expectations
The user explicitly rejected “nice enough” visuals. Treat these as hard constraints:
- The course should feel plastic and inspectable.
- The learner should be able to watch values move, not infer motion from prose.
- Graphics are not decorative. They are the lesson.
- UX must be foolproof from `START_HERE` to `COURSE_COMPLETE` .
- The first notebooks matter disproportionately. Weak early visuals destroy trust quickly.
The user also explicitly said:
- abstractions suck for this purpose
- they need to see it
- they are disappointed by pretty-but-useless pictures
Design decisions must be judged against that standard.
## Jupyter / Ops State
The Jupyter lifecycle is aligned with the cross-project manager spec.
Use `scripts/app.sh` as the source of truth:
- `bootstrap`
- `start`
- `stop`
- `restart`
- `status`
- `logs`
- compatibility:
- `validate`
- `reset-state`
Important operational constraints:
- Jupyter dirs are isolated inside the repo:
- `.jupyter_config`
- `.jupyter_data`
- `.jupyter_runtime`
- `.ipython`
- `.cache`
- `.logs`
- `.run`
- Kernel is installed with `--sys-prefix`
- Port allocation scans `8888-8899`
- PID file lives at `.logs/jupyter.pid` and mirrors to `.run/jupyter.pid`
- `start` supports background and foreground modes
- `stop` uses graceful termination before kill fallback
## Validation State
Current validation expectation:
- run `bash scripts/validate.sh` before finalizing meaningful work
Current suite count:
- `32` tests at the time this file was updated
Current test coverage includes:
- `tests/test_course_contract.py`
- notebook existence
- role / difficulty metadata
- route purity
- no raw role labels as notebook headlines
- handoff / route-nav presence
- `tests/test_notebook_execution.py`
- code cells execute as plain Python
- `tests/test_toy_ntt.py`
- math helpers
- trace examples
- round trips
- `tests/test_repo_ops.py`
- scripts / repo-local operations
- `tests/test_visuals.py`
- schoolbook HTML player behavior
- wraparound HTML stability
- non-shrinking SVG player behavior
- slider update behavior
- fixed caption-height behavior
Important truth:
- there are still no real browser-level screenshot/playback tests
- if future visual regressions keep slipping through, raising the testing bar further is a real priority
## Repo Hygiene Gotchas
This repo has one recurring trap: Jupyter notebook noise.
Running or opening tracked notebooks in Jupyter can mutate:
- execution counts
- outputs
- metadata
- cell ids
Those diffs are often not intended course changes.
Before finalizing work:
1. inspect `git diff` on dirty notebooks
2. if the diffs are only autosave / execution noise, restore them
3. only commit notebook diffs that represent intentional canonical content changes
Do not return to the user with notebook autosave noise still dirty.
Ignored local-only file:
- `Complete Beginner Guide to the Number Theoretic Transform (NTT).pdf`
It is a local reference artifact and is intentionally ignored.
## Current Restart Checklist
On a fresh restart in this repo, do this in order:
1. read `AGENT_CONTEXT.md`
2. run `git status --short --branch`
3. run `git log --oneline -8`
4. inspect the repo tree
5. if the tree is dirty, inspect diffs immediately
6. classify notebook diffs as:
- intentional canonical content changes
- or autosave / execution noise
7. summarize current state and constraints
8. continue autonomously
Before final answer:
1. run relevant tests
2. run `bash scripts/validate.sh` if the change is substantial
3. commit
4. push to `origin master`
5. verify `git status --short` is empty
## Recent Important Commits
These are useful waypoints for recovery:
- `0955ede` Ignore local reference PDF
- `934586e` Replace jittery wraparound animation
- `5f41121` Fix wraparound animation label collisions
- `b3b1885` Harden notebook animation rendering
- `5d267ee` Fix notebook headings and schoolbook UX
- `5aad355` Improve notebook chrome and player responsiveness
- `f152567` Replace early notebook plots with teaching players
- `74700b8` Add foolproof notebook route navigation
## One-Line Restart Prompt
Use this after restarting an agent in this repo:
`Read AGENT_CONTEXT.md first. Then inspect git status, git log, dirty diffs, and the repo tree, summarize the current state and constraints, clean incidental notebook noise if needed, and continue autonomously.`