Agent skill

Structured Element Extraction

by THUYRan in THUYRan/Legal-Skills-Chinese

When the AI agent must systematically analyze a legal question, case facts, legal provision, or legal relationship, it must first decompose it into a structured element checklist.

No licenceAuto-check passedTesting & QA

Install Structured Element Extraction

skills CLI
$ npx skills add THUYRan/Legal-Skills-Chinese --skill structured-element-extraction -a claude-code

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

GitHub CLI
$ gh skill install THUYRan/Legal-Skills-Chinese structured-element-extraction --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/THUYRan/Legal-Skills-Chinese.git skills-src && mkdir -p .claude/skills && cp -r skills-src/English/skills/structured-element-extraction .claude/skills/structured-element-extraction && 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
structured-element-extraction
GitHub stars
868
Token cost
~8.4k tokens
SKILL.md length
3,570 words
Files
1
Skills in repo
71
Repo updated
First seen
Licence
None found

At a glance

When the AI agent must systematically analyze a legal question, case facts, legal provision, or legal relationship, it must first decompose it into a structured element checklist.

  • Works in 4 steps: Identify Problem Type and Fix the… → Extract and Fill Elements Item by Item → Completeness Check (Triple Check) → …
  • Contract formation
  • SKILL.md covers I. Overview Table, II. Legal Disclaimer, III. Core Concepts and IV. Complete Workflow, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Structured Element Extraction is an agent skill from THUYRan/Legal-Skills-Chinese. When the AI agent must systematically analyze a legal question, case facts, legal provision, or legal relationship, it must first decompose it into a structured element checklist. Trigger this skill when: - A description of case facts is received and all legal elements must be extracted before analysis - Determining whether a legal relationship is established (e.g., contract formation, tort composition, crime composition) - Comparing similarities and differences among two or more legal facts or provisions - As a…

Its SKILL.md is about 8.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering Quality gates and Legal research.

When your agent uses it

  • Contract formation
  • Tort composition
  • Crime composition) - Comparing similarities and differences among two
  • More legal facts

Example prompts

  • “list elements,”
  • “analyze item by item,”
  • “check for omissions”
  • “/structured-element-extraction”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Identify Problem Type and Fix the Element Framework
  2. Extract and Fill Elements Item by Item
  3. Completeness Check (Triple Check)
  4. Output and Handoff

What it can do on your machine

Read from SKILL.md and the folder at commit c31ef1f. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    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

Structured Element Extraction loads about 8.4k tokens when it runs. Until then it costs about 242 tokens; SKILL.md has 3,570 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~242
When it runs · the whole SKILL.md, loaded when a task matches
~8.4k

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 3,570 words (~8,450 tokens).

“Structured elements are the result of breaking a legal question into minimal decidable units. Each element should satisfy:”

— opening of SKILL.md by THUYRan
name
structured-element-extraction

Read the full SKILL.md on GitHub

Files

Just SKILL.md in English/skills/structured-element-extraction of THUYRan/Legal-Skills-Chinese.

Open the folder on GitHubat commit c31ef1f

Compare with similar skills

Structured Element Extraction 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.

Structured Element Extraction compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Structured Element Extraction this skillTHUYRan/Legal-Skills-Chinese868—~8.4kAutomated safety check: PassNone
Feature Plannerserendipity1004/cc-feature-implementer176—~2.4kAutomated safety check: PassNone
Ccg Workflowfengshao1227/ccg-workflow5.9k—~2.3kAutomated safety check: PassMIT
Conducty Checkpointrobertbarclayy/conducty176—~1.5kAutomated safety check: PassMIT
Mission Plannerjdforsythe/forge151—~3.5kAutomated safety check: PassMIT
Quality Gate0xNyk/lacp305—~382Automated safety check: PassMIT

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    176 GitHub stars~2.4k tokensUpdated 9 mo ago
    Testing & QAAuto-check passed
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Categories

Questions about Structured Element Extraction

What does Structured Element Extraction do?

When the AI agent must systematically analyze a legal question, case facts, legal provision, or legal relationship, it must first decompose it into a structured element checklist. Structured Element Extraction is an agent skill from THUYRan/Legal-Skills-Chinese. When the AI agent must systematically analyze a legal question, case facts, legal provision, or legal relationship, it must first decompose it into a structured element checklist.

When should I use Structured Element Extraction?

Structured Element Extraction fits situations like: contract formation; tort composition; crime composition) - Comparing similarities and differences among two; more legal facts.

How do I install Structured Element Extraction in Claude Code?

Run `npx skills add THUYRan/Legal-Skills-Chinese --skill structured-element-extraction -a claude-code`. Or copy the skill folder (English/skills/structured-element-extraction in THUYRan/Legal-Skills-Chinese) into .claude/skills/structured-element-extraction in your project. Claude Code loads it when a task matches its description.

How do I install Structured Element Extraction in Codex?

Run `npx skills add THUYRan/Legal-Skills-Chinese --skill structured-element-extraction -a codex`. Or copy the skill folder (English/skills/structured-element-extraction in THUYRan/Legal-Skills-Chinese) into .agents/skills/structured-element-extraction in your project. Codex loads it when a task matches its description.

Can I use Structured Element Extraction 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 THUYRan/Legal-Skills-Chinese --skill structured-element-extraction -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/structured-element-extraction, .gemini/skills/structured-element-extraction, .github/skills/structured-element-extraction and .opencode/skills/structured-element-extraction in your project.

What does Structured Element Extraction need to run?

SKILL.md names no scripts, command-line tools or credentials: Structured Element Extraction is instructions for the agent only.

Does Structured Element Extraction 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 Structured Element Extraction 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 Structured Element Extraction use?

No licence was found for Structured Element Extraction or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Structured Element Extraction use?

About 8.4k tokens (SKILL.md is roughly 34k 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 Structured Element Extraction?

Skills that share tags, products or a category with Structured Element Extraction: Feature Planner (serendipity1004/cc-feature-implementer, 176 stars), Ccg Workflow (fengshao1227/ccg-workflow, 5.9k stars), Conducty Checkpoint (robertbarclayy/conducty, 176 stars) and Mission Planner (jdforsythe/forge, 151 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Structured Element Extraction?

THUYRan (a GitHub user) maintains it in THUYRan/Legal-Skills-Chinese, which has 868 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on August 22, 2026.

Source: THUYRan/Legal-Skills-Chinese on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.