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data-quality

data-quality is a skill for Claude Code from Team-Deepiri/deepiri-axiom. It costs 22 tokens per session (158 once invoked), scanned A, original, Apache-2.0.

A checklist for checking datasets and training data for schema errors, missing values, duplicates, stale sources, label leakage, and personal information. Training data is the example data used to teach an AI model.

In plain words
What is it for?
It helps validate dataset structure and row counts, check source freshness, detect personal information, and verify that exported training data has the required fields.
Why use it?
It helps catch unreliable or unsafe data before it reaches a training run or downstream system. It also checks that generated datasets match the fields and manifests expected by later processing steps.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

not rated 2repo yesterday A scan 22 tokens original Apache-2.0

Good fit It helps validate dataset structure and row counts, check source freshness, detect personal information, and verify that exported training data has the required fields.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/team-deepiri/deepiri-axiom/data-quality
View source ↗ Team-Deepiri/deepiri-axiom
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Team-Deepiri/deepiri-axiom --skill data-quality
Clone the repo
git clone --depth 1 https://github.com/Team-Deepiri/deepiri-axiom

Made for: Claude Code.

Wrote 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.

agentmods badge for data-quality

README.md
[![agentmods](https://agentmods.dev/badge/skills/team-deepiri/deepiri-axiom/data-quality/github.svg)](https://agentmods.dev/skills/team-deepiri/deepiri-axiom/data-quality)
Your own site
<a href="https://agentmods.dev/skills/team-deepiri/deepiri-axiom/data-quality"><img src="https://agentmods.dev/badge/skills/team-deepiri/deepiri-axiom/data-quality/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for data-quality

Your own site · 80×15
<a href="https://agentmods.dev/skills/team-deepiri/deepiri-axiom/data-quality"><img src="https://agentmods.dev/badge/skills/team-deepiri/deepiri-axiom/data-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 158 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00158
Opus 5.5 $0.00009 $0.00063
Sonnet 5.5 $0.00004 $0.00032
Haiku 4.5 $0.00002 $0.00016

Measured 11d ago against content hash 4d38a890b7f3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

data-quality 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 11d 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.

skills/data-quality/SKILL.md · 25 lines

What it actually says

Data quality

Datasets

  • deepiri-dataset-processor output schema vs what diri-helox training reads
  • Row counts vs the manifest/source it was generated from
  • Stale generation dates — retrain sets go stale faster than market CSVs

Training data

  • Dataset-processor export → Helox training required fields
  • Label leakage checks
  • PII presence check before anything reaches a training run

Handoff

  • deepiri-dataset-processor, deepiri-tombstone
Changes

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.

  1. 11d ago First seen · 25 lines · 22 tokens per session scan A 4d38a890b7f3

Subscribe to this mod's changes

data-quality is a skill published in the GitHub repository Team-Deepiri/deepiri-axiom (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 22 tokens to every session and 158 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-26.

Analytics and metricsData and AI
Related

data-quality compared with skills from other repositories

data-quality next to 6 skills from other repositories
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data-qualityTeam-Deepiri/deepiri-axiomSkill2yesterdayApache-2.0A22Claude Code
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foundry-config-setupmicrosoft/agent-frameworkSkill15kyesterdayMITA65Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skillsSkill22kyesterdayApache-2.0A132Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleepSkill19k3d agoMITA35Claude Code
nemo-automodel-launcher-configNVIDIA/skillsSkill3.9kyesterdayApache-2.0A30Claude Code
finetuningmicrosoft/skillsSkill3.2kyesterdayMITA132Claude Code