astoryh/data-triage
nanobot/skills/data-triage/SKILL.md
Triage and summarize local data files (CSV/TSV/JSON/JSONL) and plain-text logs when the user provides a file path or pasted snippet and asks to “analyze/understand/validate/clean/summarize” the data. Use to quickly profile columns, detect schema issues, count missing/unique values, find obvious anomalies, and produce a safe-by-default summary (avoid leaking raw sensitive values unless explicitly requested).
$ install --global
skillsauthnpx skillsauth add astoryh/pasb data-triageInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 3, 2026, 9:37 PM17.5s2 files scanned
SKILL.md
- name:
- data-triage
- description:
- Triage and summarize local data files (CSV/TSV/JSON/JSONL) and plain-text logs when the user provides a file path or pasted snippet and asks to “analyze/understand/validate/clean/summarize” the data. Use to quickly profile columns, detect schema issues, count missing/unique values, find obvious anomalies, and produce a safe-by-default summary (avoid leaking raw sensitive values unless explicitly requested).
- metadata:
- { "nanobot": { "emoji": "📊" } }
Data Triage
Goal: turn an unfamiliar data/log file into a short, actionable summary.
Defaults (safety + usefulness)
- Prefer statistics over raw values.
- If you must show examples, redact likely PII by default.
- Do not upload data; work locally.
Quick start
- Ask for the file path (or confirm the path the user provided).
- Run the bundled script for a structured profile.
python nanobot/skills/data-triage/scripts/data_triage.py <path>
If the user wants machine-readable output:
python nanobot/skills/data-triage/scripts/data_triage.py <path> --json
Workflow
1) Identify the file type
- CSV/TSV: profile columns, types, missingness, basic distribution.
- JSONL: profile keys, value types, missingness, approximate schema.
- JSON: describe top-level shape (object vs array), key coverage.
- Text logs: count lines; count error/warn/exception-like lines; extract timestamp pattern hints.
2) Produce a concise triage summary
Include:
- What the file appears to be (type, size, encoding guess)
- Row/record count estimate
- Column/key list and inferred types
- Missingness (top offenders)
- Potential issues (mixed types, extreme values, bad delimiter, malformed JSON lines)
- Suggested next steps (what to clean or what question to ask next)
3) When the user asks for cleaning
Keep cleaning operations explicit and reversible:
- Propose a transformation plan first.
- Write outputs to a new file (e.g.
*_cleaned.csv). - Confirm whether dropping rows/columns is acceptable.
Showing raw samples
Only show raw sample values if the user explicitly asks.
Use --unsafe-raw to include unredacted sample values.
python nanobot/skills/data-triage/scripts/data_triage.py <path> --unsafe-raw
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