flow-report
Skill67 starsChanged 6 months agoMITView on GitHub
Run a standardized 5-step quality-check and summary report on a streamflow dataset
2 other projects use a version of this.
Adopted by
Most recently taken up by
- fifersheep/flowtheir own version, first seen Oct 20, 2026
- fancylight/skillstheir own version, first seen Jul 23, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
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Wrote their own version · 2
- fancylight/skills★ 1same name
- fifersheep/flow★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository3 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- hydro-contextSkill
- run-testsSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 6
When the user invokes /flow-report or asks for a flow report, perform these five steps in order.
- Distinctive: line 27
Do not remove flagged values automatically — report them for the user to investigate
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
When the user invokes /flow-report or asks for a flow report, perform these five steps in order. Do not skip steps or reorder them.
Step 1 — Data quality check
- Count total records; count missing values (sentinel -999999 or NaN)
- Count negative discharge values (physically impossible in streamflow)
- Report the date range covered and flag any gaps longer than 7 consecutive days
Step 2 — Basic statistics (clean data only)
Exclude missing sentinels and negative values from all calculations:
- Mean, median, and standard deviation of discharge
- Minimum and maximum discharge with their dates
- Count of zero-flow days (intermittent streams may have these; perennial streams should not)
Step 3 — Annual maxima summary
- Extract one peak discharge per water year (water year N = Oct 1 of N-1 through Sep 30 of N)
- List the three highest annual peaks with their dates and water years
- Note how many complete water years are in the record
Step 4 — Outlier flag
- Compute the median of annual maxima (Q̃_annual)
- Flag any single daily or instantaneous value exceeding 5 × Q̃_annual as a potential outlier worth human review
- Do not remove flagged values automatically — report them for the user to investigate
Step 5 — Summary verdict
Assign a quality grade and print it prominently:
- GOOD: missing < 5% AND no negative values
- FAIR: missing 5–15% (no negatives)
- POOR: missing > 15% OR any negative values present
Also warn if the record contains fewer than 10 complete water years, since flood frequency estimates will be unreliable.
Format the report with a header for each step. Present statistics in a compact markdown table where possible. End with the quality grade on its own line: Data quality: GOOD / FAIR / POOR.
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