instrument-data-allotrope-validation
Sub-skill of instrument-data-allotrope: Validation.
Best use case
instrument-data-allotrope-validation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of instrument-data-allotrope: Validation.
Teams using instrument-data-allotrope-validation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/validation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How instrument-data-allotrope-validation Compares
| Feature / Agent | instrument-data-allotrope-validation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of instrument-data-allotrope: Validation.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Validation ## Validation Always validate ASM output before delivering to the user: ```bash python scripts/validate_asm.py output.json python scripts/validate_asm.py output.json --reference known_good.json # Compare to reference python scripts/validate_asm.py output.json --strict # Treat warnings as errors ``` **Validation Rules:** - Based on Allotrope ASM specification (December 2024) - Last updated: 2026-01-07 - Source: https://gitlab.com/allotrope-public/asm **Soft Validation Approach:** Unknown techniques, units, or sample roles generate **warnings** (not errors) to allow for forward compatibility. If Allotrope adds new values after December 2024, the validator won't block them--it will flag them for manual verification. Use `--strict` mode to treat warnings as errors if you need stricter validation. **What it checks:** - Correct technique selection (e.g., multi-analyte profiling vs plate reader) - Field naming conventions (space-separated, not hyphenated) - Calculated data has traceability (`data-source-aggregate-document`) - Unique identifiers exist for measurements and calculated values - Required metadata present - Valid units and sample roles (with soft validation for unknown values)
Related Skills
data-validation-reporter
Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.
worldenergydata-source-readiness
Route agents to the canonical worldenergydata source-readiness skill and summary script. Use when asked for worldenergydata data completeness, data locations, latest known data dates, scheduler freshness, source-readiness status, or acceptance-criteria inputs across the repo ecosystem.
sodir-data-extractor
Extract and process Norwegian Petroleum Directorate field and production data from SODIR
metocean-data-fetcher
Fetch real-time and historical metocean data from NDBC, CO-OPS, Open-Meteo, ERDDAP, and MET Norway. Use for buoy data retrieval, tidal observations, marine forecasts, and multi-source data fusion.
energy-data-visualizer
Interactive visualization for oil and gas production data analysis using Plotly dashboards
bsee-data-extractor
Extract and process BSEE (Bureau of Safety and Environmental Enforcement) data including production, WAR (Well Activity Reports), and APD (Application for Permit to Drill) data. Use for querying production data, well activities, drilling permits, completions, and workovers by API number, block, lease, or field with automatic data normalization and caching.
gtm-demo-validation-cache-regression-repair
Diagnose and repair GTM demo validation failures caused by legacy cache files missing intermediate chart data, especially in nested digitalmodel demo scripts using --from-cache.
tax-return-data-capture-and-archival
Capture structured tax return summaries as YAML for year-over-year comparison, with fallback to manual PDF download and relocation when automation fails
repo-separation-for-sensitive-data
Architecture pattern for splitting confidential data and reusable algorithms across repos
plan-gated-issue-validation-workflow
Systematic validation pattern for plan-approved GitHub issues with pre-existing deliverables
metadata-only-wiki-sweep-workflow
Disciplined inventory process for cataloging documents by filename/path without content claims, using parent-centric grouping to prevent stub proliferation
metadata-only-inventory-sweep
Execute constrained file inventory sweeps with metadata-only stubs and validation, useful for staged documentation work on large file sets