technical_figure_understanding

technical_figure_understanding is a skill for Claude Code, Codex from equinor/neqsim. It costs 0 tokens per session (1,225 once invoked), scanned A, original, Apache-2.0.

A method for examining engineering figures closely enough to explain their visual evidence, meaning, and relevance in a book, paper, or report.

In plain words
What is it for?
It helps interpret plots, process diagrams, flow maps, equipment sketches, case-study layouts, decision matrices, and source-document figures.
Why use it?
It prevents figures from being treated as decoration and supports explanations grounded in plotted data, diagrams, captions, and surrounding context.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps interpret plots, process diagrams, flow maps, equipment sketches, case-study layouts, decision matrices, and source-document figures.

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Install with agentmods
npx agentmods add skills/equinor/neqsim/technical_figure_understanding
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 equinor/neqsim --skill technical_figure_understanding
Clone the repo
git clone --depth 1 https://github.com/equinor/neqsim

Made for: Claude Code, Codex.

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 technical_figure_understanding

README.md
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Your own site
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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 technical_figure_understanding

Your own site · 80×15
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Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,225 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00000 $0.01225
Opus 5 $0.00000 $0.00613
Sonnet 5 $0.00000 $0.00245
Haiku 4.5 $0.00000 $0.00122

Measured 6d ago against content hash dbf4393745b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

technical_figure_understanding 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 6d 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.

neqsim-paperlab/skills/technical_figure_understanding/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Technical Figure Understanding

Purpose

Read engineering figures deeply enough that a book, paper, or report can explain what the figure shows and why it matters. This skill complements figure-discussion: this skill extracts and classifies visual evidence; figure-discussion turns that evidence into observation, mechanism, implication, and recommendation prose.

Use this skill for lecture slides, notebook plots, process diagrams, flow maps, equipment sketches, case-study layouts, decision matrices, and source-document figures that need to be placed into textbook or engineering-report context.

Inputs

For every figure, gather as many of these inputs as available:

Input Examples
Image file figures/ch04_s06_ipr_vlp.png
Existing caption or alt text Markdown image alt text, results.json.figure_captions
Source metadata lecture folder, PPTX slide, PDF page, notebook path, generated script
Surrounding text preceding and following chapter paragraphs
Chapter plan chapter_outlines.yaml, learning objectives, section heading
Computed data notebook outputs, results.json, CSV tables

Figure Classes

Classify the figure before writing about it:

Class What to extract
Plot axes, units, scales, legend, trends, extrema, intersections, thresholds
Flow map axes, operating points, regime boundaries, transition risks
Process diagram unit operations, stream directions, recycle loops, control signals
Layout/map distance, route, host/tieback relationships, bottlenecks
Decision matrix options, criteria, dominant trade-off, ranking
Equipment sketch internals, dimensions, physical function, design constraint
Table screenshot row/column headers, numeric values, units, caveats
Cover/decorative art topic signalling only; usually exempt from discussion gate
Photo/corporate image provenance and rights check before inclusion

Read the full file on GitHub · 130 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. 6d ago First seen · 130 lines · 0 tokens per session scan A dbf4393745b6

Subscribe to this mod's changes

technical_figure_understanding is a skill published in the GitHub repository equinor/neqsim (151 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,225 tokens. 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 2026-09-03.

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