Revise paper prose and publish reproducible sources

README.md

@@ -21,7 +21,7 @@ configs:
 
 Author and contact: **EnvLoop Research — research@envloop.ai**.
 
-The [paper](recursive-play-paper.pdf) explains the task construction, fixed-budget evaluation, matched-case examples, uncertainty and prospective improvement pathway. This release contains task metadata, executable environment source and selected outcome tables. It contains no model weights, complete training trajectories or measured training/RSI gain.
+The [paper](recursive-play-paper.pdf) explains the task construction, fixed-budget evaluation, matched-case examples, uncertainty and prospective improvement pathway. The [editable source](paper-source.zip) places `main.tex` at the archive root and preserves its relative `staging/` and `figures/` paths. It contains no authoring runtime, operational evidence or private checks. This release contains task metadata, executable environment source and selected outcome tables. It contains no model weights, complete training trajectories or measured training/RSI gain.
 
 ## Files and configurations
 
@@ -35,7 +35,8 @@ The [paper](recursive-play-paper.pdf) explains the task construction, fixed-budg
 | `challenge-tasks.jsonl` | Fifteen tasks left unfinished by every configuration, with exact completion-depth vectors |
 | `challenge-inventory.json` | Existing curated evidence for those fifteen tasks and the canonical reference validation |
 | `environment-source.zip` | Ten source modules plus their standard-library-only interface, registry and generation plan |
-| `recursive-play-paper.pdf` | The current 24-page English paper |
+| `recursive-play-paper.pdf` | The revised 24-page English paper with complete explanatory prose |
+| `paper-source.zip` | Exactly 38 LaTeX compilation inputs: `main.tex`, included sections, bibliography, five vector figures and twenty recorded PNGs |
 | `SHA256SUMS.txt` | File hashes for this release payload |
 
 The Hub `tasks` configuration reads `tasks.jsonl`; `results` reads `episodes.jsonl` for a consistent JSON builder. `episodes.csv` remains the unmodified authoritative CSV. The JSONL is a lossless cell-for-cell projection: no fields, identifiers, scores or empty values are changed or coerced. Both use a `test` split label for organisation. This bank was exposed during development: **that label does not make it a sealed or independent held-out test set.** No train/validation partition or new training labels are fabricated.

SHA256SUMS.txt

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paper-source.zip

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+size 371887

recursive-play-paper.pdf

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