Frictionless Tabular Validation Starter
A Claude skill from ma-compbio-lab/SkillFoundry.
Install
$ agentstack add skill-ma-compbio-lab-skillfoundry-frictionless-tabular-validation-starter ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-ma-compbio-lab-skillfoundry-frictionless-tabular-validation-starter) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Frictionless Tabular Validation Starter
Use this skill to validate a small CSV or TSV table against a simple Frictionless schema and emit a compact machine-readable error summary.
What it does
- loads a tabular input file plus a JSON schema descriptor
- runs
frictionlessvalidation from the repo-manageddata-toolsprefix - reports row counts, field names, and normalized validation errors
When to use it
- you need a verified starter for
data-validation - you want a deterministic schema-validation smoke fixture for tabular scientific data
- you need structured validation output before downstream ingestion or conversion
Example
./slurm/envs/data-tools/bin/python skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/scripts/run_frictionless_tabular_validation.py \
--input skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/examples/toy_people_valid.csv \
--schema skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/examples/toy_people_schema.json \
--out scratch/data-validation/frictionless_summary.jsonVerification
- Skill-local tests:
python3 -m unittest discover -s skills/data-acquisition-and-dataset-handling/frictionless-tabular-validation-starter/tests -p 'test_*.py' - Expected valid summary:
valid == true,row_count == 3,error_count == 0
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: ma-compbio-lab
- Source: ma-compbio-lab/SkillFoundry
- License: Apache-2.0
- Homepage: https://ma-compbio-lab.github.io/SkillFoundry/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.