agentleFS
IamK77IamK77/Skill/skills/atelier/color/SKILL.md

color

Skill2 starsChanged 32 days agoApache-2.0View on GitHub

Explore palette ideas through perception, material associations, temperature, and semantic relationships. Use for generative colour thinking; contrast measurements are optional instruments, not taste gates.

8 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 8 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Keep one colour fixed and change its surroundings.

    line 36
  2. Distinctive:

    Use the coherence probe on a rendered candidate if useful.

    line 46
  3. Distinctive:

    Read selectively when a thread needs another perspective or a concrete technique.

    line 50

“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md
<!-- Copyright 2026 IamK77 — Licensed under the Apache License, Version 2.0. See ./LICENSE and ./NOTICE · https://www.apache.org/licenses/LICENSE-2.0 -->

color

Explore palette ideas through perception, material associations, temperature, and semantic relationships. Use for generative colour thinking; contrast measurements are optional instruments, not taste gates.

Starting point

Colour is relational: a quiet hue can become loud in the right company. Explore what the palette makes possible before turning it into a fixed ramp.

Bring a question, fragment, reference, or tension. Follow whichever association becomes useful; these invitations are not a sequence to complete. Speculation should remain distinguishable from an observed fact.

Thought experiments

Move the light source

Imagine the same subject under morning light, a monitor glow, and reflected water. Translate those relationships into background, foreground, and accent possibilities.

Give colour a grammar

Try colour as material identity, emotional punctuation, or data meaning. Explore what should remain neutral under each grammar.

Change the neighbour

Keep one colour fixed and change its surroundings. Discover a direction through interaction rather than collecting attractive swatches independently.

A possible turn

A dark interface need not be a daytime palette inverted. A night-observatory metaphor suggests restrained luminous marks on cool darkness; a theatre metaphor suggests warm pools of attention. Both can be explored before choosing and measuring actual text/background pairs.

Leave the space open

Offer a few genuinely different possibilities, a sketch, an analogy, or a sharper question when useful. Do not turn every prompt into a scored diagnostic, a completion gate, or a demand for an action plan. The human may choose a direction, combine them, or leave the question open.

Use the coherence probe on a rendered candidate if useful. It measures declared relationships, not aesthetic merit; implementation still needs context-appropriate accessibility checks.

Optional references

Read selectively when a thread needs another perspective or a concrete technique. The notes supply possibilities, examples, and limits; none is a prerequisite or a requirement to close the exploration.

  • Working with colour coordinates
  • Contrast, endpoints, and useful distinctions
  • A dark theme as a separate mapping
  • Colour that matches the data relationship
  • Palette recipes as experiments

Probe usage and limits. Probes remain optional and do not create a creative checklist run.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.