Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ma-compbio-lab/SkillFoundrynpx agentmods add skills/ma-compbio-lab/skillfoundry/frictionless-tabular-validation-starterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/frictionless-tabular-validation-starter)<a href="https://agentmods.dev/skills/ma-compbio-lab/skillfoundry/frictionless-tabular-validation-starter"><img src="https://agentmods.dev/badge/skills/ma-compbio-lab/skillfoundry/frictionless-tabular-validation-starter.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.00307 |
| Opus 5 | $0.00000 | $0.00153 |
| Sonnet 5 | $0.00000 | $0.00061 |
| Haiku 4.5 | $0.00000 | $0.00031 |
Grade A, and why
frictionless-tabular-validation-starter scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
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.json
Verification
- 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
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/toy_people_valid_summary.json 437 B
- examples/toy_people_invalid.csv 76 B
- examples/toy_people_schema.json 153 B
- examples/toy_people_valid.csv 68 B
- metadata.yaml 1.6 KB
- refs.md 139 B
- scripts/run_frictionless_tabular_validation.py 2.8 KB runs code
- tests/test_run_frictionless_tabular_validation.py 3.2 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 30 lines · 0 tokens per session scan A f9a8a5fee12c
frictionless-tabular-validation-starter is a skill published in the GitHub repository ma-compbio-lab/SkillFoundry (38 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 307 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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