docs: refine public positioning for precipitation diagnostics

README.md

@@ -4,7 +4,7 @@ This repository is a portfolio space for scientific-computing infrastructure,
 systems tooling, and supply-chain-security experiments that favor deterministic
 behavior, auditable outputs, and clear release evidence.
 
-## Current Flagship Project
+## Current Flagship Tool
 
 [`tools/sbom-diff-and-risk`](tools/sbom-diff-and-risk/README.md) is the
 current flagship tool. It compares SBOMs and dependency manifests, produces
@@ -14,13 +14,13 @@ can optionally record PyPI provenance and OpenSSF Scorecard evidence.
 For a fast reviewer overview, start with the [`sbom-diff-and-risk` reviewer
 brief](tools/sbom-diff-and-risk/docs/reviewer-brief.md).
 
-## Additional Project
+## Supporting Spatiotemporal Diagnostics Project
 
 [`projects/precipitation-anomaly-diagnostics`](projects/precipitation-anomaly-diagnostics/README.md)
-is a public-safe climate diagnostics mini-lab. It demonstrates a reproducible
-workflow for precipitation anomaly preprocessing, EOF analysis, representative
-year selection, circulation composites, and reviewer-friendly scientific
-interpretation.
+is a public-safe scientific-data diagnostics mini-lab. It demonstrates a
+reproducible workflow for precipitation anomaly preprocessing, EOF analysis,
+representative-period selection, composite analysis, and reviewer-friendly
+scientific interpretation.
 
 ## Why This Repository Exists
 
@@ -65,6 +65,9 @@ What to review:
 Sanitized climate-diagnostics workflow, small derived example artifacts,
 methodology notes, data policy, and synthetic-data tests.
 
+This mini-lab is a supporting scientific-data project and is not part of the
+`sbom-diff-and-risk` release surface.
+
 Useful entry points:
 
 - [`precipitation-anomaly-diagnostics` README](projects/precipitation-anomaly-diagnostics/README.md)

projects/precipitation-anomaly-diagnostics/PUBLICATION_BOUNDARIES.md

@@ -0,0 +1,17 @@
+# Publication Boundaries
+
+This public module is a sanitized scientific-computing artifact.
+
+It excludes:
+
+- institution names;
+- course names;
+- instructor or team-member names;
+- student identifiers;
+- original reports, slides, and submission files;
+- raw third-party climate datasets;
+- local machine paths;
+- private working archives.
+
+The public value of this project is the reproducible diagnostics workflow, not
+the original academic context.

projects/precipitation-anomaly-diagnostics/README.md

@@ -1,17 +1,22 @@
-# Precipitation Anomaly Diagnostics Lab
+# Precipitation Anomaly Diagnostics
 
-A compact scientific-computing workflow for July precipitation anomaly diagnostics over eastern China.
+A compact spatiotemporal diagnostics module for reproducible precipitation
+anomaly analysis.
 
-This mini-lab demonstrates how to turn gridded precipitation and atmospheric circulation fields into reproducible climate diagnostics:
+This project demonstrates how to turn gridded scientific data into a
+reviewable analysis workflow:
 
-- preprocess monthly precipitation and circulation fields;
-- compute climatology, anomalies, and standardized anomaly indices;
-- apply EOF analysis to identify dominant spatial modes;
-- select representative years from standardized principal components;
-- run circulation composite analysis for positive and negative phases;
-- generate reviewable figures and lightweight Markdown reports.
+- preprocessing and quality-preserving subsetting;
+- climatology, anomaly, and standardized-index construction;
+- dimensionality reduction with EOF analysis;
+- representative-period selection from standardized time coefficients;
+- composite analysis for contrasting phases;
+- reviewable figures and lightweight Markdown reports.
 
-The repository is designed as a reproducible research mini-lab, not as an operational forecast system.
+The repository is designed as a reproducible research mini-lab, not as an
+operational forecast system. Domain-specific choices such as the target month,
+region, and variables are documented as configurable analysis context rather
+than as the public identity of the project.
 
 ## Repository Layout
 
@@ -27,6 +32,7 @@ The repository is designed as a reproducible research mini-lab, not as an operat
 ├─ examples/
 │  ├─ regional_precipitation_summary_1961_2022.csv
 │  └─ sample_metadata.json
+├─ PUBLICATION_BOUNDARIES.md
 ├─ reports/example-report.md
 ├─ scripts/
 │  ├─ run_composite_analysis.py
@@ -40,6 +46,15 @@ The repository is designed as a reproducible research mini-lab, not as an operat
    └─ preprocess.py
 ```
 
+## Reviewer Path
+
+1. Read [`docs/data-policy.md`](docs/data-policy.md) for public data boundaries.
+2. Read [`PUBLICATION_BOUNDARIES.md`](PUBLICATION_BOUNDARIES.md) for identity and publication boundaries.
+3. Read [`docs/methodology.md`](docs/methodology.md) for the analysis workflow.
+4. Read [`docs/inference-framework.md`](docs/inference-framework.md) for the reasoning chain.
+5. Skim [`reports/example-report.md`](reports/example-report.md) for the public-facing output.
+6. Inspect [`tests/`](tests/) for synthetic-data behavior checks.
+
 ## Installation
 
 Use Python 3.10+.
@@ -78,7 +93,9 @@ python scripts/run_eof_analysis.py --config configs/example.yaml
 python scripts/run_composite_analysis.py --config configs/example.yaml
 ```
 
-The example CSV under `examples/` is a small derived summary table for demonstration only. It is not a raw dataset.
+The example CSV under `examples/` is a small derived demonstration artifact.
+It is not a raw dataset, a canonical dataset release, or a substitute for
+provider-sourced scientific data.
 
 ## Demonstration Figures
 

projects/precipitation-anomaly-diagnostics/pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "precipitation-anomaly-diagnostics"
 version = "0.1.0"
-description = "A public-safe scientific-computing mini-lab for precipitation anomaly diagnostics."
+description = "A public-safe spatiotemporal diagnostics module for reproducible precipitation anomaly analysis."
 readme = "README.md"
 requires-python = ">=3.10"
 license = { text = "MIT" }