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.
npx skills add ClarentCinematics/Codex-Skills-for-Enterprise --skill data-quality-triagegit clone --depth 1 https://github.com/ClarentCinematics/Codex-Skills-for-EnterpriseWrote 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/clarentcinematics/codex-skills-for-enterprise/data-quality-triage)<a href="https://agentmods.dev/skills/clarentcinematics/codex-skills-for-enterprise/data-quality-triage"><img src="https://agentmods.dev/badge/skills/clarentcinematics/codex-skills-for-enterprise/data-quality-triage/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.
<a href="https://agentmods.dev/skills/clarentcinematics/codex-skills-for-enterprise/data-quality-triage"><img src="https://agentmods.dev/badge/skills/clarentcinematics/codex-skills-for-enterprise/data-quality-triage.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00069 | $0.00485 |
| Opus 5 | $0.00034 | $0.00243 |
| Sonnet 5 | $0.00014 | $0.00097 |
| Haiku 4.5 | $0.00007 | $0.00049 |
Grade A, and why
data-quality-triage 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 10d 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
Data Quality Triage
Workflow
- Identify dataset purpose, grain, source date, key fields, date fields, and business use.
- Detect missing values, duplicate records, stale dates, inconsistent categories, and schema gaps.
- Separate deterministic data-quality findings from metric interpretation or business conclusions.
- Prioritize risks by downstream impact on reporting, operations, decisions, and automation.
- Recommend cleanup actions, source-system checks, and owner questions.
Script-Assisted Workflow
When given a CSV sample, run scripts/audit_data_quality.py --input <csv> before writing the triage. Add --key-fields, --date-fields, --stale-days, and --today when the dataset contract is known. Use --json for structured evidence. Do not let the helper infer missing values, metric definitions, or business truth.
Output Standard
Use this structure by default:
- Triage Summary: dataset, scope, row count, and overall quality risk.
- Critical Findings: duplicate keys, high-null fields, stale dates, schema blockers, or enum conflicts.
- Field-Level Evidence: field, issue, examples, and affected count or rate.
- Downstream Risk: dashboard, metric, workflow, or decision impact.
- Cleanup Actions: source-system checks, owner actions, and validation queries.
- Questions To Resolve: missing grain, key, owner, metric definition, or freshness context.
- Caveats: sample limitations and non-inferred fields.
Rules
- Do not invent missing values, metric definitions, row ownership, or source-of-truth status.
- Mark sample-based findings as sample-based.
- Treat high-impact reporting, finance, customer, or compliance data as requiring human review.
- Prefer deterministic checks before narrative interpretation.
References
Read references/data-quality-rubric.md when prioritizing findings or mapping data-quality risks to reporting, automation, or operational impact.
What ships with it
3 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.
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.
- 10d ago First seen · 42 lines · 69 tokens per session scan A d0acd409fbf4
data-quality-triage is a skill published in the GitHub repository ClarentCinematics/Codex-Skills-for-Enterprise (2 stars, last pushed 2mo ago), licensed MIT. It adds 69 tokens to every session and 485 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
Other skills, from other repositories
adapto-scaffold
Create a new Adapto-ready frontend by wrapping npx create-adapto-app — choose a framework (Next/Astro/SvelteKit), scaffold the project (the Adapto read-client is included), and wire up .env. Consent-gated — shows the exact command and runs it only after you approve. New projects only.
adapto-translate
Translate existing Adapto content (Articles, Pages, collection items, Categories, Microcopy) into another enabled language via create-translation. Structural-parity gate blocks broken translations; glossary-aware; single-item and corpus modes. Plan-then-apply; runs at the top model tier.
adapto-content-upload
Push approved content drafts to Adapto — convert each reviewed Markdown draft to HTML, create or update the Article/Page/collection item (one-way push via the ledger id-map), mirror its SEO metadata into adaptoseo, and drift-guard against out-of-band CMS edits. Schema-gated; everything lands as draft. Plan-then-apply.
adapto-project-define
Build the project's "brain" — a rich, local multi-file knowledge base — through deep guided discovery (a short skippable interview plus active web/competitor/keyword research), and store a summary in Adapto as adaptoprojectconfig so every other skill writes on-brand. Plan-then-apply; fully optional.
adapto-schema-apply
Apply an approved .adapto/schema-plan.json to the CMS — create Article categories and custom collections (with a two-pass step for references), idempotently, via the adapto CLI. Plan-then-apply; writes content. Pairs with adapto:schema-design.
adapto-microcopy
Manage UI micro copy (nav, buttons, labels, errors) as Adapto key/value/language entries. Two modes — init seeds a curated, on-brand starter set; extract scans your frontend for hardcoded strings and creates entries + a replacement guide (no source rewrite). Plan-then-apply.