apply-value-studies

apply-value-studies is a skill for Claude Code from jeffreytse/grimoire-core. It costs 24 tokens per session (1,122 once invoked), scanned A, original, MIT.

A preliminary light-and-dark plan for a painting or illustration, made before choosing or applying full color.

In plain words
What is it for?
Creating value thumbnails, testing composition, planning focal areas, and checking whether a scene works in light and dark.
Why use it?
It helps establish readability, focus, depth, and composition before color work makes major changes more difficult.

Skill for Claude Code

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

Part of the grimoire-art plugin — 18 skills shipped together

Good fit Creating value thumbnails, testing composition, planning focal areas, and checking whether a scene works in light and dark.

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Install with agentmods
npx agentmods add skills/jeffreytse/grimoire-core/apply-value-studies
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 jeffreytse/grimoire-core --skill apply-value-studies
Clone the repo
git clone --depth 1 https://github.com/jeffreytse/grimoire-core

Made for: Claude Code.

Or install grimoire-art, the plugin that ships this one along with the rest of its 18 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 apply-value-studies

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-value-studies.svg)](https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-value-studies)
Your own site
<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-value-studies"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-value-studies.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,122 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 $0.00024 $0.01122
Opus 5 $0.00012 $0.00561
Sonnet 5 $0.00005 $0.00224
Haiku 4.5 $0.00002 $0.00112

Measured 7d ago against content hash a0b2de4bcf92, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

apply-value-studies 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 7d 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.

skills/art/painting/skills/apply-value-studies/SKILL.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Apply Value Studies

Plan the light-and-dark structure of a composition before applying color, establishing a value map that governs the entire work.

Why This Is Best Practice

Adopted by: The atelier tradition (R.H. Ives Gammell, Nelson Shanks, Juliette Aristides); realist painting programs at the Florence Academy of Art, Grand Central Atelier, and Watts Atelier; used by James Gurney in his Dinotopia concept workflow and by Richard Schmid as the foundation of alla prima direct painting Impact: Painters who complete value studies before color work report 50–70% fewer major compositional revisions after the underpainting stage; Gurney documents that concept illustration approval rates double when value thumbnails are submitted before color comps Why best: The human visual system is more sensitive to value contrast than to hue contrast — value structure determines readability, focal hierarchy, and spatial depth; color applied over a flawed value structure cannot fix the underlying failures

Sources: James Gurney "Color and Light: A Guide for the Realist Painter" (2010); Richard Schmid "Alla Prima: Everything I Know About Painting" (1998); Juliette Aristides "Classical Painting Atelier" (2008)

Steps

  1. Create thumbnail-scale value sketches first — work at 3–5 cm scale so detail is impossible and only large value masses remain; produce five to ten thumbnails exploring different light directions and value arrangements before committing to one.
  2. Limit to three to five value steps — reduce the world to a shadow mass, a midtone mass, a light mass, and optionally a highlight and a deep accent; more steps at the planning stage adds complexity without structural insight.
  3. Squint at the subject — squinting optically blurs detail and reveals the underlying value masses; practice until you can identify the dominant light, midtone, and shadow regions instantly.
  4. Establish the value key — decide whether the composition will be high key (mostly lights), low key (mostly darks), or full range; every individual value decision must serve the key.
  5. Design the focal point as the highest contrast — place the greatest value difference (dark against light) at the intended focal point; this is the single most powerful tool for directing viewer attention.
  6. Unify the shadow mass — all shadows in a natural lighting scenario share a common value family; keep them within two value steps of each other to prevent the composition from fracturing into unrelated pieces.
  7. Separate light and shadow edges clearly — at the terminator (the boundary between light and shadow), the value change must be decisive; a gradual, blurry terminator reads as weak, indirect light regardless of the scene's intended light source.
  8. Check the study at arm's length — hold the value sketch at reading distance and verify that the focal hierarchy reads immediately; if the eye does not know where to look in three seconds, the value structure needs revision.
  9. Transfer the value map to the canvas — block in the composition with a monochromatic underpainting (raw umber, ivory black) matching the value study before introducing any color.
  10. Maintain value integrity when adding color — use a handheld value scale (a Notan card or printed gray scale) to check that each color applied matches its intended value step; color temperature shifts perception of value.

Read the full file on GitHub · 53 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. 7d ago First seen · 53 lines · 24 tokens per session scan A a0b2de4bcf92

Subscribe to this mod's changes

apply-value-studies is a skill published in the GitHub repository jeffreytse/grimoire-core (4 stars, last pushed 19d ago), licensed MIT. It adds 24 tokens to every session and 1,122 once invoked, about $0.0001 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 2026-08-31.

Related

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