| name | check-csvs |
| description | Use when the user wants a data-quality review of the generated CSV files in public/, especially after fetch-data or stitching changes. Audit the current CSV set for duplicates, date/order issues, suspicious jumps, stitch-boundary continuity, and cross-file consistency using DataFetch.md and scripts/fetch-data.ts as the source of truth. |
Check CSVs
Use this skill to sanity-check the generated CSV files in public/.
Current files to audit:
etf-upro.csv
etf-tqqq.csv
etf-sso.csv
etf-qld.csv
index-sp.csv
index-nq.csv
risk-sgov.csv
risk-vgsh.csv
risk-gldm.csv
risk-brka.csv
rate-borrow.csv
inflation.csv
Do not expect rate-tbill-1m.csv or rate-treasury-2y.csv; those were removed.
Source of truth
Before reviewing anomalies, read:
DataFetch.md
- relevant sections of
scripts/fetch-data.ts
If the prompt, docs, and code disagree, treat the code as the source of truth.
Checks
-
Structural sanity
- No duplicate dates.
- Dates strictly increase.
- Expected columns exist for each file type.
- Values are finite and positive where required.
-
Gap sanity
- Daily files: gaps should be plausible market/weekend/holiday gaps.
- Inflation: monthly cadence should be consistent.
- Flag long unexplained gaps.
-
Stitch-boundary continuity
- Focus on source/name transitions, not normal movement inside one segment.
- Check that boundary prices are continuous after scaling.
- Use
name and source changes plus fetch-data.ts boundary logic to identify expected stitch points.
-
Suspicious jumps
- ETFs / indices: flag implausible one-day jumps.
- SGOV / VGSH: very small daily moves expected.
- GLDM: moderate commodity moves only.
- Borrow rate / inflation: gradual changes expected.
- Use common sense; review context before calling a move wrong.
-
Cross-file consistency
- Leveraged ETFs should broadly move with their underlying index direction.
- SGOV and VGSH should look treasury-like.
- Stitched proxy behavior should make sense relative to the live asset after transitions.
Review method
- Start with lightweight checks:
- header
- first/last rows
- duplicate dates
- largest daily moves
- source/name transitions
- Then inspect only the suspicious windows in detail.
- Prefer explaining whether an anomaly is:
- expected by stitch design
- a likely data bug
- or uncertain and needs manual verification
Output
For each issue found, report:
- file
- issue type
- exact date/rows involved
- why it is suspicious
- likely fix or next verification step
If no issues are found, say that explicitly and mention what you checked.