qfoldit-oilgas

qfoldit-oilgas is a skill for Claude Code from qfoldit/Protein-Design-MCP. It costs 135 tokens per session (1,034 once invoked), scanned A, original, Apache-2.0.

A calculation method for estimating internal carbon-dioxide corrosion in carbon-steel oil and gas pipelines and the time before the pipe wall may become too thin. It combines a published corrosion formula with factors such as temperature, flow, salinity, protective scale, and inhibitor use.

In plain words
What is it for?
Use it with temperature, CO2 pressure, flow speed, salinity, and inhibitor information to estimate corrosion rate, remaining wall life, flow-related erosion-corrosion risk, and salinity-related pitting risk.
Why use it?
It provides a structured estimate when assessing corrosion risk, while documenting that its generic literature values are not calibrated to a specific pipeline unless field data is supplied.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the qfoldit-skills plugin — 20 skills shipped together

Good fit Use it with temperature, CO2 pressure, flow speed, salinity, and inhibitor information to estimate corrosion rate, remaining wall life, flow-related erosion-corrosion risk, and salinity-related pitting risk.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/qfoldit/protein-design-mcp/oilgas
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 qfoldit/Protein-Design-MCP --skill oilgas
Clone the repo
git clone --depth 1 https://github.com/qfoldit/Protein-Design-MCP

Made for: Claude Code.

Or install qfoldit-skills, the plugin that ships this one along with the rest of its 20 skills.

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 qfoldit-oilgas

README.md
[![agentmods](https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/oilgas/github.svg)](https://agentmods.dev/skills/qfoldit/protein-design-mcp/oilgas)
Your own site
<a href="https://agentmods.dev/skills/qfoldit/protein-design-mcp/oilgas"><img src="https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/oilgas/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 qfoldit-oilgas

Your own site · 80×15
<a href="https://agentmods.dev/skills/qfoldit/protein-design-mcp/oilgas"><img src="https://agentmods.dev/badge/skills/qfoldit/protein-design-mcp/oilgas.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 135 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,034 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 $0.00135 $0.01034
Opus 5.5 $0.00054 $0.00414
Sonnet 5.5 $0.00027 $0.00207
Haiku 4.5 $0.00014 $0.00103

Measured 2mo ago against content hash 516a183d072a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

qfoldit-oilgas 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 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/corrosion_kinetics.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

claude-skills/skills/oilgas/SKILL.md · 78 lines

How it starts

The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.

qfoldit-oilgas (corrosion)

Kinetic/empirical model for internal CO2 corrosion of carbon steel oil & gas pipelines, built on the published de Waard-Milliams correlation plus three well-documented secondary effects: protective FeCO3 scale suppression at higher temperature, flow-driven mass-transfer enhancement (with an erosion-corrosion regime at high velocity), and a chloride/ salinity-driven pitting risk indicator.

Read references/model_documentation.md before answering -- it has the full equations, the model's valid range, calibration status, and critical caveats (the base correlation and secondary-effect parameters are generic literature values, not fitted to any specific qFoldIT pipeline/field until real coupon/ER-probe/field data is supplied).

How to handle a request

  1. Gather inputs: temperature (C), CO2 partial pressure (bar) -- estimate from total pressure x CO2 mole fraction if not given directly -- flow velocity (m/s), salinity (ppt, default seawater ~35 if offshore/produced-water context implies it), and whether a corrosion inhibitor is in use (and its claimed efficiency, typically 80-95% if properly maintained -- ask rather than assume if not stated).
  2. Validate ranges: the de Waard-Milliams correlation's empirical basis is roughly T=5-150C, pCO2=0.1-10 bar. Flag extrapolation outside this rather than presenting it with the same confidence.
  3. Run scripts/corrosion_kinetics.py: predict_corrosion_rate(...) for the uniform corrosion rate + pitting risk factor; remaining_life_years(...) if wall thickness is known or asked about.
  4. Always separate uniform corrosion rate from pitting risk -- they are different corrosion modes (general metal loss vs. localized perforation risk) and should never be combined into one number or implied to be interchangeable.
  5. State calibration status with any numeric forecast: the base correlation is a widely-used published one, but the scale-suppression and flow-enhancement terms are simplified approximations calibrated to generic literature shapes, not to any specific pipeline. If the user has field/coupon corrosion data, use fit_dewaard_offset_from_data to calibrate a site-specific correction factor before forecasting.
  6. Remaining-life estimates assume a constant rate -- flag this explicitly; real field conditions (water cut, temperature, inhibitor availability) change over time, so this is a first-order screening number, not a substitute for an inspection program.
  7. The flow/mass-transfer factor here is a deliberately simplified proxy, not a reproduction of the full de Waard 1995 Sherwood-type mass-transfer equation (which needs diffusion coefficient, viscosity, and hydraulic diameter -- inputs this skill doesn't collect). It captures the same two qualitative behaviors (mass-transfer-limited at low velocity, erosion-corrosion above an erosional threshold) but should not be presented as numerically equivalent to the full published model. Say so if asked how this compares to NORSOK M-506 or the full de Waard 1995 equation.

Read the full file on GitHub · 78 lines

Files

What ships with it

5 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.

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. 2mo ago First seen · 78 lines · 135 tokens per session scan A 516a183d072a

Subscribe to this mod's changes

qfoldit-oilgas is a skill published in the GitHub repository qfoldit/Protein-Design-MCP (1 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 135 tokens to every session and 1,034 once invoked, about $0.0005 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 2026-08-31.

Related

qfoldit-oilgas compared with skills from other repositories

qfoldit-oilgas next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
qfoldit-oilgasqfoldit/Protein-Design-MCPSkill12mo agoApache-2.0A135Claude Code
instrument-data-to-allotropeanthropics/knowledge-work-pluginsSkill35ktodayApache-2.0A123Claude Code
exploratory-data-analysisK-Dense-AI/scientific-agent-skillsSkill56k5d agoMITA83Claude Code
matlabK-Dense-AI/scientific-agent-skillsSkill56k5d agoMITA44Claude Code
phylogeneticsK-Dense-AI/scientific-agent-skillsSkill56k5d agoMITA71Claude Code, Codex
research-engineerdavila7/claude-code-templatesSkill33ktodayMITA43Claude Code, Codex
mapping-to-snomedmaziyarpanahi/openmedSkill5.8ktodayApache-2.0A205Claude Code