profile
Skill84 starsChanged 13 days agoMITView on GitHub
Use when a new source or new files arrive, to profile them before any data contract or pipeline code is written, the file formats, the schema, the data quality, the bad records, the relationships, the gaps and the personal data.
29 other projects use a version of this.
Adopted by
Most recently taken up by
- nockawa/NockMontheir own version, first seen Nov 8, 2026
- galiprandi/job-seekertheir own version, first seen Nov 5, 2026
- cismontane-harris2642/signal-prospecting-kittheir own version, first seen Nov 1, 2026
- YahyaLendani/opus-tuner-claude-skilltheir own version, first seen Nov 1, 2026
- r-rogozin/chessprinttheir own version, first seen Oct 25, 2026
- julienamorgan/signal-prospecting-kittheir own version, first seen Oct 25, 2026
Used with
Projects with it also use apply, coverage and 4 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
proficientlyjobsSkillapply
Fill out a job application on Greenhouse, Lever, or Workday
Also in 3 projects that use this
PydanticSkillcoverage
Fetch coverage diff from Codecov for the current branch or a specific PR. Shows uncovered lines, patch coverage, and overall coverage change.
Also in 3 projects that use this
dragonflydbSkillbenchmark
Benchmark Dragonfly (and compare against Valkey/Redis) on local or remote cloud instances, then produce a performance + memory report with charts and a raw-data appendix. Use this whenever the user runs /benchmark, or asks to benchmark / load-test / measure throughput, QPS, latency, or memory efficiency of Dragonfly or another Redis-compatible server, to compare Dragonfly vs Valkey or Redis, or to generate a benchmark report. Trigger it even when the user just describes the goal ("see how fast Dragonfly is on this box", "compare memory per key vs Valkey") without saying the word "benchmark".
Also in 3 projects that use this
AnthropicSkillstatus
Case status summary by audience — client-facing (plain language), internal (for the professor), or court-ready (formal caption format per local rules). Same facts, different framing and depth. Use when a student needs to update the client, brief the professor, or prepare a court status report.
Also in 3 projects that use this
VercelSkillsetup
Set up Vercel CLI and project configuration. Use when the user says "set up Vercel", "configure Vercel", "link to Vercel", or "vercel init".
Also in 3 projects that use this
GoogleSkilltdd
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
Also in 3 projects that use this
Other versions29 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 29
- ccusage/ccusage★ 19ksame name
- ryoppippi/ccusage★ 19ksame name
- FalkorDB/FalkorDB★ 10ksame name
- pytorch/executorch★ 5.2ksame name
- verl-project/verl-omni★ 1.5ksame name
- nockawa/Typhon★ 253same name
- galiprandi/job-seeker★ 120same name
- the-void-ia/void-box★ 88same name
- Flemma-Dev/flemma.nvim★ 57same name
- baekenough/oh-my-customcode★ 42same name
19 more not listed
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 repository16 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- big-reviewSkill
- contractSkill
- cost-reviewSkill
- data-productSkill
- docsSkill
- impactSkill
- incidentSkill
- knowledge-refreshSkill
- metadataSkill
- migrationSkill
- pr-reviewSkill
- qualitySkill
- reconcileSkill
- test-dataSkill
- toolkitSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 23 edited versions we read keep these.
4
Distinctive
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 15
Run a profiler on what arrived, with scripts that count.
- Distinctive: line 41
Never changes a file of the project.
- Distinctive: line 42
Never guesses a format: a format is what the values show.
- Distinctive: line 43
Never shows personal data unmasked.
“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Profile
The job: understand new data before anything is built on it. It writes nothing but the report.
Input: the folder of the new source, a feed file, or a table.
Steps
- Run a profiler on what arrived, with scripts that count. Never guess a number.
- File format: delimiter, quoting, encoding, null tokens, decimal separators, date and timestamp formats.
- Schema: tables, columns, data types, row counts, and the schema drift between the files.
- Data quality: null values, empty columns, constant columns, duplicate rows, and the uniqueness of the primary key.
- Bad records: corrupt records, outliers, values out of range, and placeholder values such as 9999-12-31.
- Relationships: for every foreign key, the orphans, the child rows whose parent is not in the delivery.
- Gaps and deletes: business days without rows, tables that never change, and how the source marks a deleted row.
- Personal data: the columns that hold personal or bank data, with their values masked on the page.
- Compare with the metadata, if there is one: columns the metadata does not know, and columns that did not arrive.
- Rank the findings, each with the rows it affects and the decision it needs, marked for the data contract or for the pipeline.
- Give the result as one web page, with the input for the data contract and the pipeline at the end.
Output
One HTML file, like references/profile.html: the numbers on top, one section per check with a chart or a table, the findings ranked, and the input for the contract and the pipeline last. Read it for the layout before you write the page.
Reads
- the files or tables, read-only, and the metadata if there is one
Writes
- the web page only
Never
- Never changes a file of the project.
- Never guesses a format: a format is what the values show.
- Never shows personal data unmasked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.