data-qc-reviewer

data-qc-reviewer is an agent for Claude Code from SteadfastAsArt/geoscience-skills. It costs 41 tokens per session (1,096 once invoked), scanned A, original, MIT.

Instructions for checking the quality of geoscience datasets, including well logs, seismic data, and spatial data. They define domain-specific checks for unusual or physically implausible values.

In plain words
What is it for?
Use them when loading LAS or DLIS well logs, SEG-Y seismic files, or spatial datasets, and when deciding which geoscience tools to use before analysis.
Why use it?
They help catch bad, missing, or suspicious measurements before those data are used in later analysis.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

Good fit Use them when loading LAS or DLIS well logs, SEG-Y seismic files, or spatial datasets, and when deciding which geoscience tools to use before analysis.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/steadfastasart/geoscience-skills/data-qc-reviewer
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.

Clone the repo
git clone --depth 1 https://github.com/SteadfastAsArt/geoscience-skills

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-qc-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/agents/steadfastasart/geoscience-skills/data-qc-reviewer/github.svg)](https://agentmods.dev/agents/steadfastasart/geoscience-skills/data-qc-reviewer)
Your own site
<a href="https://agentmods.dev/agents/steadfastasart/geoscience-skills/data-qc-reviewer"><img src="https://agentmods.dev/badge/agents/steadfastasart/geoscience-skills/data-qc-reviewer/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-qc-reviewer

Your own site · 80×15
<a href="https://agentmods.dev/agents/steadfastasart/geoscience-skills/data-qc-reviewer"><img src="https://agentmods.dev/badge/agents/steadfastasart/geoscience-skills/data-qc-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 41 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,096 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 $0.00041 $0.01096
Opus 5 $0.00020 $0.00548
Sonnet 5 $0.00008 $0.00219
Haiku 4.5 $0.00004 $0.00110

Measured 10d ago against content hash 2d16d3d0ae74, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

data-qc-reviewer 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.

agents/data-qc-reviewer.md · 87 lines

How it starts

The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role

Geoscience data QC specialist that checks loaded data for domain-specific quality issues. When a user loads a new dataset or prepares data for an analysis pipeline, run the relevant QC checks below and report findings. Flag anomalies early to prevent garbage-in-garbage-out problems downstream.

Relevant Skills

Use data-qc-reviewer alongside these skills from the library:

  • lasio and dlisio for loading well log files before QC
  • segyio for loading seismic data before QC
  • welly for well-level analysis after QC passes
  • verde and geostatspy for spatial data that requires QC first

Well Log QC Checks

Apply these range checks to standard petrophysical curves after loading LAS or DLIS files:

  • GR (Gamma Ray): 0-300 API units. Values above 300 may indicate hot shales or tool malfunction.
  • RHOB (Bulk Density): 1.0-3.0 g/cc. Values outside this range are non-physical for sedimentary rocks.
  • NPHI (Neutron Porosity): -0.05 to 0.60 v/v. Negative values are valid in gas zones but flag for review.
  • DT (Sonic Transit Time): 40-200 us/ft. Values outside this range suggest tool failure or extreme lithology.
  • RT/ILD (Resistivity): 0.1-10000 ohm.m on a log scale. Zero or negative values are invalid.
  • CALI (Caliper): Compare against bit size. Flag washouts where CALI exceeds bit size by more than 2 inches.
  • Depth: Must be monotonically increasing with regular sampling. Flag gaps, duplicates, or irregular steps.
  • Null values: Check for -999.25 (standard LAS null) and NaN. Report null percentage per curve. Flag curves with more than 30% nulls as potentially unusable.

Seismic QC Checks

Apply these checks when loading SEG-Y or other seismic data formats:

  • Dead/zero traces: Calculate percentage of all-zero traces. More than 5% warrants investigation.
  • Amplitude statistics: Report min, max, mean, std, and RMS amplitude. Look for outliers indicating bad traces or scaling issues.
  • Geometry validation: Verify inline/crossline ranges and spacing are consistent. Check for a regular grid without gaps.
  • Sample interval consistency: All traces must share the same dt. Mixed intervals indicate corruption or bad merges.
  • Trace length consistency: All traces should have the same number of samples. Variable lengths need investigation.
  • Header completeness: Verify CDP, offset, coordinates, and inline/crossline numbers are populated.

Read the full file on GitHub · 87 lines

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. 10d ago First seen · 87 lines · 41 tokens per session scan A 2d16d3d0ae74

Subscribe to this mod's changes

data-qc-reviewer is an agent published in the GitHub repository SteadfastAsArt/geoscience-skills (58 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 1,096 once invoked, about $0.0002 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 2026-08-30.

Related

Other agents, from other repositories

editor

Journal editor who desk-reviews manuscripts, selects two referees with deliberately different dispositions, calibrates to a target journal from .claude/references/journal-profiles.md, and synthesizes an editorial decision (FATAL / ADDRESSABLE / TASTE). Used by /review-paper --peer [journal].

pedrohcgs/claude-code-my-workflow · 64 tokens

Geoprocessing Specialist

ArcPy and Python toolbox expert who automates spatial workflows — builds .pyt toolboxes, Model Builder processes, batch geoprocessing automation, and custom analysis scripts for ArcGIS Pro.

SHAdd0WTAka/Zen-Ai-Pentest · 45 tokens

research-scout

Scans the NeqSim codebase to discover scientific paper opportunities that will drive code improvement. Every paper must improve NeqSim — adding tests, validating models against data, hardening algorithms, or implementing new capabilities. Produces ranked, actionable topics that feed into the planner agent.

equinor/neqsim · 61 tokens

epidemiology-research-agent

Research agent for epidemiology and public health.

benbrastmckie/nvim · 8 tokens

gpd-plan-checker

Verifies plans will achieve phase goal before execution. Goal-backward analysis of plan quality for physics research. Spawned by the plan-phase and verify-work workflows.

psi-oss/get-physics-done · 38 tokens

ma-output-consultant

Engage when the question is what output wrote, or the process dir must be regenerated because a choice is fixed at generation time and no card edit undoes it: helicity recycling (runcard helrecycling=False does NOT cure a compile-time Line truncated; only output --helrecycling=False does), its auto-disable for a…

MadGraphTeam/MadAgents · 202 tokens