Agent skill

Fidelity Scoring

by epoko77-ai in epoko77-ai/design-diversity

팩 렌더를 원본 레퍼런스와 페이지 단위로 대조해 '원문 충실도'를 0~4점 7축으로 채점하고 합격·반려를 판정하는 방법론 스킬.

Custom licenceAuto-check passed

Install Fidelity Scoring

skills CLI
$ npx skills add epoko77-ai/design-diversity --skill fidelity-scoring -a claude-code

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

GitHub CLI
$ gh skill install epoko77-ai/design-diversity fidelity-scoring --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/epoko77-ai/design-diversity.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/fidelity-scoring .claude/skills/fidelity-scoring && 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
fidelity-scoring
GitHub stars
192
Token cost
~1.4k tokens
SKILL.md length
716 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
Custom licence

At a glance

팩 렌더를 원본 레퍼런스와 페이지 단위로 대조해 '원문 충실도'를 0~4점 7축으로 채점하고 합격·반려를 판정하는 방법론 스킬.

  • Works in 4 steps: 원본은 보수적 네이비 문서인데 결과가 네온 포스터 → diversity… → 원본이 baseline과 원래 비슷하면, 정확히 재현한 결과가… → 색·타이포·레이아웃 값이 같아도 시그니처 모티프·페이지 순서·차트… → …
  • SKILL.md covers diversity와 fidelity는 다른 것을 잰다, 적용 대상, 입력 (검증자 방화벽) and 7축 루브릭 (각 0~4점, 총 28점), plus 7 more sections
  • Calls codex

What it does

Fidelity Scoring is an agent skill from epoko77-ai/design-diversity. 팩 렌더를 원본 레퍼런스와 페이지 단위로 대조해 '원문 충실도'를 0~4점 7축으로 채점하고 합격·반려를 판정하는 방법론 스킬. fidelity-qa 에이전트가 사용한다. diversity-scoring(baseline 대비 차별성)과 역할이 다르며 서로를 대체할 수 없다. 변환 계약 이행률·시그니처 재현율·환각 요소 검출·관계 문법· 주목 위계·데이터 무결성·권리 경계 7축과 이종 모델 교차검증 절차를 규정한다.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Claude Code 산출물의 디자인 다양성 확보 — 공개 디자인 시스템을 증류한 프롬프트형 디자인 팩 100종 카탈로그 (PPT 50 + 웹 50).

Example prompts

  • “/fidelity-scoring”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 원본은 보수적 네이비 문서인데 결과가 네온 포스터 → diversity 만점, fidelity 0점.
  2. 원본이 baseline과 원래 비슷하면, 정확히 재현한 결과가 diversity에서 반려된다.
  3. 색·타이포·레이아웃 값이 같아도 시그니처 모티프·페이지 순서·차트 의미·반복 규칙이 틀릴 수 있다.
  4. pHash·색 히스토그램·엣지 밀도는 "무엇이 어디에 왜 있는가"를 판정하지 못한다.

What it can do on your machine

Read from SKILL.md and the folder at commit efb4ca6. 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

    Shell commands in SKILL.md call:

    • codex

    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

Fidelity Scoring loads about 1.4k tokens when it runs. Until then it costs about 63 tokens; SKILL.md has 716 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~63
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 716 words (~1,424 tokens).

“fidelity-qa가 "이 팩이 실제로 원본을 닮았는가"를 판정하는 방법.”

— opening of SKILL.md by epoko77-ai, Custom licence
name
fidelity-scoring

Read the full SKILL.md on GitHub

Files

Just SKILL.md in .claude/skills/fidelity-scoring of epoko77-ai/design-diversity.

Open the folder on GitHubat commit efb4ca6

Compare with similar skills

Fidelity Scoring 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.

Fidelity Scoring compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Fidelity Scoring this skillepoko77-ai/design-diversity192—~1.4kAutomated safety check: PassCustom licence
Claw Scoreopenclaw/openclaw392k—~2.5kAutomated safety check: PassMIT
Harness Scoreruvnet/ruflo74k—~605Automated safety check: NotesMIT
Score Evalsickn33/agentic-awesome-skills47k1 repos~304Automated safety check: PassMIT
UI Scoresickn33/agentic-awesome-skills47k1 repos~1.8kAutomated safety check: PassMIT
Fidel API AutomationComposioHQ/awesome-claude-skills77k3 repos~738Automated safety check: PassNone

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Questions about Fidelity Scoring

What does Fidelity Scoring do?

팩 렌더를 원본 레퍼런스와 페이지 단위로 대조해 '원문 충실도'를 0~4점 7축으로 채점하고 합격·반려를 판정하는 방법론 스킬. Fidelity Scoring is an agent skill from epoko77-ai/design-diversity. 팩 렌더를 원본 레퍼런스와 페이지 단위로 대조해 '원문 충실도'를 0~4점 7축으로 채점하고 합격·반려를 판정하는 방법론 스킬.

How do I install Fidelity Scoring in Claude Code?

Run `npx skills add epoko77-ai/design-diversity --skill fidelity-scoring -a claude-code`. Or copy the skill folder (.claude/skills/fidelity-scoring in epoko77-ai/design-diversity) into .claude/skills/fidelity-scoring in your project. Claude Code loads it when a task matches its description.

How do I install Fidelity Scoring in Codex?

Run `npx skills add epoko77-ai/design-diversity --skill fidelity-scoring -a codex`. Or copy the skill folder (.claude/skills/fidelity-scoring in epoko77-ai/design-diversity) into .agents/skills/fidelity-scoring in your project. Codex loads it when a task matches its description.

Can I use Fidelity Scoring 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 epoko77-ai/design-diversity --skill fidelity-scoring -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fidelity-scoring, .gemini/skills/fidelity-scoring, .github/skills/fidelity-scoring and .opencode/skills/fidelity-scoring in your project.

What does Fidelity Scoring need to run?

Going by SKILL.md and its folder, Fidelity Scoring needs the command-line tools its instructions call (codex).

Does Fidelity Scoring 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 Fidelity Scoring 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 Fidelity Scoring use?

Fidelity Scoring has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Fidelity Scoring use?

About 1.4k tokens (SKILL.md is roughly 5.7k 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 Fidelity Scoring?

Skills that share tags, products or a category with Fidelity Scoring: Claw Score (openclaw/openclaw, 392k stars), Harness Score (ruvnet/ruflo, 74k stars), Score Eval (sickn33/agentic-awesome-skills, 47k stars) and UI Score (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fidelity Scoring?

epoko77-ai (a GitHub user) maintains it in epoko77-ai/design-diversity, which has 192 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on August 16, 2026.

Source: epoko77-ai/design-diversity on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.