Agent skill

Abstraction Concrete Examples

by lyndonkl in lyndonkl/claude

Builds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels.

No licenceAuto-check passedAI & LLM Engineering

Install Abstraction Concrete Examples

skills CLI
$ npx skills add lyndonkl/claude --skill abstraction-concrete-examples -a claude-code

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

GitHub CLI
$ gh skill install lyndonkl/claude abstraction-concrete-examples --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/lyndonkl/claude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/abstraction-concrete-examples .claude/skills/abstraction-concrete-examples && 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
abstraction-concrete-examples
GitHub stars
164
Token cost
~1.1k tokens
SKILL.md length
417 words
Files
6
Skills in repo
12
Repo updated
First seen
Licence
None found

At a glance

Builds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels.

  • Explaining concepts at different expertise levels
  • SKILL.md covers Table of Contents, Workflow, Common Patterns and Guardrails, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Moving between abstract principles and concrete implementation

What it does

Abstraction Concrete Examples is an agent skill from lyndonkl/claude. Builds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels. Bridges communication gaps, reveals hidden assumptions, and tests whether abstract ideas work in practice. Use when explaining concepts at different expertise levels, moving between abstract principles and concrete implementation, identifying edge cases by testing ideas against scenarios, designing layered documentation, decomposing complex problems into actionable steps, or bridging…

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files (for example `resources/evaluators/rubric_abstraction_concrete_examples.json`, `resources/examples/api-design.md` and `resources/examples/hiring-process.md`).

It sits in AI & LLM Engineering. The repository describes itself as: Agents, skills and anything else to use with claude.

When your agent uses it

  • Explaining concepts at different expertise levels
  • Moving between abstract principles and concrete implementation
  • Identifying edge cases by testing ideas against scenarios
  • Designing layered documentation

Example prompts

  • “Use the abstraction-concrete-examples skill to build structured abstraction ladders that translate high-level principles into concrete, actionable…”
  • “/abstraction-concrete-examples”

What it can do on your machine

Read from SKILL.md and the folder at commit 4acc337. 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.

    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

Abstraction Concrete Examples loads about 1.1k tokens when it runs. Until then it costs about 143 tokens; SKILL.md has 417 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~143
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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 417 words (~1,145 tokens).

“The ladder uses 3-5 levels connecting universal principles to concrete details. Example:”

— opening of SKILL.md by lyndonkl
name
abstraction-concrete-examples

Read the full SKILL.md on GitHub

Files

SKILL.md and 5 other files in skills/abstraction-concrete-examples of lyndonkl/claude.

  • SKILL.md
  • resources/evaluators/rubric_abstraction_concrete_examples.json
  • resources/examples/api-design.md
  • resources/examples/hiring-process.md
  • resources/methodology.md
  • resources/template.md

Open the folder on GitHubat commit 4acc337

Compare with similar skills

Abstraction Concrete Examples 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.

Abstraction Concrete Examples compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Abstraction Concrete Examples this skilllyndonkl/claude164—~1.1kAutomated safety check: PassNone
Agent BuildershareAI-lab/learn-claude-code78k4 repos~1.2kAutomated safety check: PassMIT
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs13k8 repos~3.3kAutomated safety check: PassMIT
1passwordtrpc-group/trpc-agent-go1.9k14 repos~656Automated safety check: PassApache-2.0

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Questions about Abstraction Concrete Examples

What does Abstraction Concrete Examples do?

Builds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels. Abstraction Concrete Examples is an agent skill from lyndonkl/claude. Builds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels.

When should I use Abstraction Concrete Examples?

Abstraction Concrete Examples fits situations like: explaining concepts at different expertise levels; moving between abstract principles and concrete implementation; identifying edge cases by testing ideas against scenarios; designing layered documentation.

How do I install Abstraction Concrete Examples in Claude Code?

Run `npx skills add lyndonkl/claude --skill abstraction-concrete-examples -a claude-code`. Or copy the skill folder (skills/abstraction-concrete-examples in lyndonkl/claude) into .claude/skills/abstraction-concrete-examples in your project. Claude Code loads it when a task matches its description.

How do I install Abstraction Concrete Examples in Codex?

Run `npx skills add lyndonkl/claude --skill abstraction-concrete-examples -a codex`. Or copy the skill folder (skills/abstraction-concrete-examples in lyndonkl/claude) into .agents/skills/abstraction-concrete-examples in your project. Codex loads it when a task matches its description.

Can I use Abstraction Concrete Examples 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 lyndonkl/claude --skill abstraction-concrete-examples -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/abstraction-concrete-examples, .gemini/skills/abstraction-concrete-examples, .github/skills/abstraction-concrete-examples and .opencode/skills/abstraction-concrete-examples in your project.

What does Abstraction Concrete Examples need to run?

SKILL.md names no scripts, command-line tools or credentials: Abstraction Concrete Examples is instructions for the agent only.

Does Abstraction Concrete Examples 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 Abstraction Concrete Examples 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 Abstraction Concrete Examples use?

No licence was found for Abstraction Concrete Examples or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Abstraction Concrete Examples use?

About 1.1k tokens (SKILL.md is roughly 4.6k 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 Abstraction Concrete Examples?

Skills that share tags, products or a category with Abstraction Concrete Examples: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Abstraction Concrete Examples?

lyndonkl (a GitHub user) maintains it in lyndonkl/claude, which has 164 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 1, 2026.

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