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Agent skill

Hdr Test Pattern Generation

by clshortfuse in clshortfuse/renodx

RenoDX workflow for generating HDR/SDR test patterns, synthetic charts, ramps, gradients, hue sweeps, color bars, checkerboards, banding panels, gamut stress images, BT.709/BT.2020/AP1 comparisons…

MITAuto-check passed

Install Hdr Test Pattern Generation

skills CLI
$ npx skills add clshortfuse/renodx --skill hdr-test-pattern-generation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install clshortfuse/renodx hdr-test-pattern-generation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/clshortfuse/renodx.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/hdr-test-pattern-generation .claude/skills/hdr-test-pattern-generation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hdr-test-pattern-generation
GitHub stars
4.4k
Token cost
~1.3k tokens
SKILL.md length
590 words
Files
2
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

RenoDX workflow for generating HDR/SDR test patterns, synthetic charts, ramps, gradients, hue sweeps, color bars, checkerboards, banding panels, gamut stress images, BT.709/BT.2020/AP1 comparisons…

  • Making test pattern images
  • SKILL.md covers Boundaries, First classify the pattern goal, Source domain checklist and Useful pattern families, plus 3 more sections
  • Runs Python scripts from its folder
  • Datasets for tonemap

What it does

Hdr Test Pattern Generation is an agent skill from clshortfuse/renodx. RenoDX workflow for generating HDR/SDR test patterns, synthetic charts, ramps, gradients, hue sweeps, color bars, checkerboards, banding panels, gamut stress images, BT.709/BT.2020/AP1 comparisons, and scalar/energy-map validation sources. Use when making test pattern images or datasets for tonemap, gamut, LUT, PsychoV, RenoDRT, HDR, or cICP validation.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `templates/hdr_pattern_template.py`).

The repository describes itself as: Renovation Engine for DirectX Games. The licence is MIT.

When your agent uses it

  • Making test pattern images
  • Datasets for tonemap
  • CICP validation

Example prompts

  • “/hdr-test-pattern-generation”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 374d07b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hdr Test Pattern Generation loads about 1.3k tokens when it runs. Until then it costs about 96 tokens; SKILL.md has 590 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from clshortfuse/renodx at commit 374d07b, republished under its MIT licence (© clshortfuse). 590 words, ~1,345 tokens.

Download SKILL.mdSave it as .claude/skills/hdr-test-pattern-generation/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
hdr-test-pattern-generation
description
RenoDX workflow for generating HDR/SDR test patterns, synthetic charts, ramps, gradients, hue sweeps, color bars, checkerboards, banding panels, gamut stress images, BT.709/BT.2020/AP1 comparisons, and scalar/energy-map validation sources. Use when making test pattern images or datasets for tonemap, gamut, LUT, PsychoV, RenoDRT, HDR, or cICP validation.
argument-hint
pattern type, source gamut/transfer, nits or linear range, dimensions, output format, and validation target

HDR Test Pattern Generation

Use this small skill for creating source patterns and synthetic datasets. Larger skills should reference it instead of embedding pattern design rules.

Boundaries

  • Focus on generating deterministic test inputs: ramps, sweeps, charts, masks, and diagnostic images.
  • Use analysis-graphing for plots of pattern statistics or transform curves.
  • Use bt2020-png-generation when the final deliverable is a BT.2020 PQ RGB16 PNG with cICP or HDR ICC metadata.
  • Keep one-off experiments in a scratch output path; promote repeated generators or durable fixtures to tools/analysis/ or the relevant test asset folder.
  • Do not silently reuse an existing image if the task needs a controlled source domain; document the source gamut, transfer, white point, and value units.

First classify the pattern goal

Before generating pixels, state what the pattern is intended to expose:

  • Tone-map shape, shoulder, toe, mid-gray, or diffuse-white behavior.
  • Gamut mapping, hue preservation, negative-channel clipping, or out-of-gamut handling.
  • LUT precision, tetrahedral/trilinear interpolation, or banding.
  • PQ/HLG/SDR transfer correctness and viewer metadata behavior.
  • Spatial artifacts: edge halos, checkerboard instability, bloom thresholds, sharpening, or temporal reprojection.
  • Scalar/energy maps for RenoDRT/PsychoV/N2 reapply experiments.

Source domain checklist

Every pattern needs explicit metadata in the script, filename, or sidecar stats:

FieldExamples
Gamut / primariesBT.709, BT.2020, AP1, AP0
White pointD65, D60, adapted D60→D65
Transferscene-linear, display-linear nits, sRGB, PQ
Value scale0..1, stops around 1.0, absolute nits, diffuse-white-relative
Bit depth / formatEXR float, RGB16 PNG, 8-bit preview PNG/WebP
Clipping policypreserve negatives for stats, clip only at output, hard clip to gamut, mask out-of-gamut

Do not normalize pattern maxima unless normalization is the experiment.

Useful pattern families

PatternUse forNotes
Neutral ramp / step wedgeTone curves, PQ quantization, bandingInclude fine ramp plus labeled stops or nits steps.
Hue sweepGamut compression and hue preservationSweep hue in a known gamut; keep saturation/value and luminance assumptions explicit.
Primary/secondary chipsBT.709/BT.2020/AP1 comparisonInclude white/gray references and expected out-of-gamut chips.
OOG stress chartNegative channels, over-1 values, matrix/adaptation errorsPreserve unclipped stats before output clipping.
Banding panel8-bit/10-bit/16-bit path checksUse smooth ramps plus small-amplitude perturbations when needed.
Checker/edge patternSpatial filters, bloom, sharpening, TAA artifactsInclude hard edges and subpixel-aligned variants if relevant.
Synthetic scene chartEnd-to-end tone/gamut validationKeep source EXR and rendered outputs together.
Scalar/energy mapN2/RenoDRT/PsychoV energy diagnosticsReplicate to RGB only at the final visualization/export step.
Show full SKILL.md (205 more words)Show less

Output guidance

  • Prefer EXR float for source fixtures that must preserve scene-linear or out-of-range values.
  • Use ordinary SDR PNG only for quick human previews or SDR-specific tests.
  • Use BT.2020 PQ RGB16 PNG plus cICP only for HDR delivery or viewer-signaling tests.
  • Keep stats beside generated outputs: min/max, nonfinite count, negative channels, over-range channels, chosen nits mapping, and source domain.
  • Name files with the important domain choices, for example bt709_linear_hue_sweep, bt2020_hdr_pq_100nits, or syntheticChart_rec709_finite.

Existing references

  • HDR pattern template for deterministic ramps, hue sweeps, and sidecar stats.
  • tests/D3D12HDR-test/images/syntheticChart_rec709.01.exr for a recurring synthetic chart source.
  • tests/D3D12HDR-test/images/RGB_sweep_smooth_31x50.exr for RGB sweep validation.
  • tools/analysis/synthetic_neutwo_energy_reapply_bt2020.py for synthetic chart to BT.2020 HDR output workflow.
  • tools/analysis/validate_mb_compress.py for BT.2020 hue sweep validation patterns.
  • tools/analysis/syntheticChart_rec709_finite/ for generated comparisons and stats.

Common mistakes to avoid

  • Do not mix BT.709, BT.2020, AP1, and AP0 values without naming the conversion path.
  • Do not apply sRGB transfer to data that is already linear or PQ.
  • Do not PQ-encode twice.
  • Do not clip negative or out-of-gamut values before recording diagnostics unless clipping is the behavior being tested.
  • Do not rely on screenshots as validation assets when exact pixels or metadata matter.
  • Do not create a new pattern generator when an existing source fixture or script already covers the same controlled case.

© clshortfuse, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in .agents/skills/hdr-test-pattern-generation of clshortfuse/renodx.

  • SKILL.md
  • templates/hdr_pattern_template.py

Open the folder on GitHubat commit 374d07b

Compare with similar skills

Hdr Test Pattern Generation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Hdr Test Pattern Generation compared with similar skills
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Kotlin Exposed Patternsaffaan-m/ECC275k4 repos~5.5kAutomated safety check: PassMIT
Generatealirezarezvani/claude-skills28k1 repos~1.1kAutomated safety check: PassMIT
Dotnet Patternsaffaan-m/ECC275k1 repos~2.3kAutomated safety check: PassMIT
Fastapi Patternsaffaan-m/ECC275k—~2.3kAutomated safety check: PassMIT

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Questions about Hdr Test Pattern Generation

What does Hdr Test Pattern Generation do?

RenoDX workflow for generating HDR/SDR test patterns, synthetic charts, ramps, gradients, hue sweeps, color bars, checkerboards, banding panels, gamut stress images, BT.709/BT.2020/AP1 comparisons…. Hdr Test Pattern Generation is an agent skill from clshortfuse/renodx.2020/AP1 comparisons, and scalar/energy-map validation sources.

When should I use Hdr Test Pattern Generation?

Hdr Test Pattern Generation fits situations like: making test pattern images; datasets for tonemap; CICP validation.

How do I install Hdr Test Pattern Generation in Claude Code?

Run `npx skills add clshortfuse/renodx --skill hdr-test-pattern-generation -a claude-code`. Or copy the skill folder (.agents/skills/hdr-test-pattern-generation in clshortfuse/renodx) into .claude/skills/hdr-test-pattern-generation in your project. Claude Code loads it when a task matches its description.

How do I install Hdr Test Pattern Generation in Codex?

Run `npx skills add clshortfuse/renodx --skill hdr-test-pattern-generation -a codex`. Or copy the skill folder (.agents/skills/hdr-test-pattern-generation in clshortfuse/renodx) into .agents/skills/hdr-test-pattern-generation in your project. Codex loads it when a task matches its description.

Can I use Hdr Test Pattern Generation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add clshortfuse/renodx --skill hdr-test-pattern-generation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hdr-test-pattern-generation, .gemini/skills/hdr-test-pattern-generation, .github/skills/hdr-test-pattern-generation and .opencode/skills/hdr-test-pattern-generation in your project.

What does Hdr Test Pattern Generation need to run?

Going by SKILL.md and its folder, Hdr Test Pattern Generation needs Python for the scripts in its folder. Our summary lists: Python 3.

Does Hdr Test Pattern Generation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Hdr Test Pattern Generation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hdr Test Pattern Generation use?

Hdr Test Pattern Generation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hdr Test Pattern Generation use?

About 1.3k tokens (SKILL.md is roughly 5.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hdr Test Pattern Generation?

Skills that share tags, products or a category with Hdr Test Pattern Generation: Golang Patterns (affaan-m/ECC, 275k stars), Kotlin Exposed Patterns (affaan-m/ECC, 275k stars), Generate (alirezarezvani/claude-skills, 28k stars) and Dotnet Patterns (affaan-m/ECC, 275k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hdr Test Pattern Generation?

clshortfuse (a GitHub user) maintains it in clshortfuse/renodx, which has 4,445 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 8, 2026.

Source: clshortfuse/renodx on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.