New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Explain

by kv0906 in kv0906/pm-kit

Break down complex concepts (math, models, systems, terminology) into first-principles explanations.

MITAuto-check passed

Install Explain

skills CLI
$ npx skills add kv0906/pm-kit --skill explain -a claude-code

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

GitHub CLI
$ gh skill install kv0906/pm-kit explain --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/kv0906/pm-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/explain .claude/skills/explain && 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
explain
GitHub stars
138
Token cost
~941 tokens
SKILL.md length
508 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

Break down complex concepts (math, models, systems, terminology) into first-principles explanations.

  • Works in 7 steps: What This Produces → What Controls It → Reverse Walkthrough (End → Beginning) → …
  • User says explain
  • SKILL.md covers What You Do, Input, Reasoning Process (follow in… and Output Structure, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Explain is an agent skill from kv0906/pm-kit. Break down complex concepts (math, models, systems, terminology) into first-principles explanations. Use when user says "explain", "break this down", "first principles", "ELI5", or pastes a formula/model/system to understand.

Its SKILL.md is about 940 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: AI-augmented PM workspace for Coding Agents — daily standups, decisions, blockers, docs, and sprint reviews as markdown skills. The licence is MIT.

When your agent uses it

  • User says explain
  • Break this down
  • First principles
  • Pastes a formula/model/system to understand

Example prompts

  • “explain”
  • “break this down”
  • “first principles”
  • “/explain”

Workflow steps

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

  1. What This Produces
  2. What Controls It
  3. Reverse Walkthrough (End → Beginning)
  4. What Each Part Measures (and Why)
  5. Rules of the Game
  6. Concrete Example
  7. One-Paragraph Summary

What it can do on your machine

Read from SKILL.md and the folder at commit 2cb5d9f. 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

Explain loads about 941 tokens when it runs. Until then it costs about 58 tokens; SKILL.md has 508 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~941

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

The full file from kv0906/pm-kit at commit 2cb5d9f, republished under its MIT licence (© kv0906). 508 words, ~941 tokens.

Download SKILL.mdSave it as .claude/skills/explain/SKILL.md (or your agent's skills folder).
name
explain
description
Break down complex concepts (math, models, systems, terminology) into first-principles explanations. Use when user says "explain", "break this down", "first principles", "ELI5", or pastes a formula/model/system to understand.

Explain — First Principles Concept Breaker

Reverse-engineer complex concepts into natural language. No jargon. Start from the end result and work backwards to raw inputs.

Input format: /explain [concept, formula, model, or paste]

What You Do

Take any complex input — math formula, scoring model, system design, methodology, technical concept — and explain it so a beginner can explain it back.

Input

User provides:

  • A math problem, equation, methodology, scoring system, model, or abstract concept
  • Optional: context of what it's used for (finance, physics, prediction markets, etc.)

Reasoning Process (follow in order)

Work through these steps internally before writing the explanation:

A. Find the End Goal — What is the final output? Translate it to a real-world result (money, score, probability, decision, ranking).

B. Find the Inputs — What raw information goes in? Translate each to real-world meaning.

C. Find How Value Is Earned — What actions/factors increase the result? What decreases it?

D. Find Comparisons — Does the model compare things? (person vs person, side vs side, time vs time). Explain as "share of total" or "relative contribution".

E. Find Rules and Boundaries — Minimums, maximums, penalties, special cases. Explain why each exists.

F. Find Time/Repetition — If the model samples repeatedly, explain as "measured many times and added up over time."

G. Find What Breaks Without Each Piece — For each major component, ask: what goes wrong if we remove this? This reveals WHY it exists.

Output Structure

Write these sections in order:

1. What This Produces

One sentence: what the final output represents in real life.

2. What Controls It

List the real-world factors that push the result up or down. No symbols.

3. Reverse Walkthrough (End → Beginning)

Start from the final result. Walk backwards through each layer until reaching raw inputs. Each step should answer: "where does THIS come from?"

Show full SKILL.md (214 more words)Show less
4. What Each Part Measures (and Why)

For each component:

  • What it measures in plain language
  • Why it exists (what breaks without it)
  • What behavior it rewards or punishes
5. Rules of the Game

Rewrite the entire model as a rulebook using "If you do X, then Y happens" statements. No math.

6. Concrete Example

Small example with simple numbers. Show how changing one input changes the outcome.

7. One-Paragraph Summary

Compress everything into one short paragraph a beginner could repeat back.

Style Rules

  • Short sentences. Natural wording.
  • No symbols unless user insists.
  • No jargon: avoid "quadratic", "normalization", "distribution", "convex", "derivative", "expectation", "linear regression" etc.
  • When jargon is unavoidable, immediately follow with a plain restatement: "normalization — meaning we shrink everything to fit on the same scale"
  • Use everyday metaphors: sharing a pie, scoring a game, competition ranking, filling a bucket.
  • Prioritize meaning over calculation.
  • Write to a file in docs/ when output exceeds 20 lines (per vault conventions).

Fail-Safes

If the input is ambiguous or missing definitions:

  • Make the best interpretation
  • State assumptions explicitly
  • Still explain the likely intent

Success Criteria

Your explanation succeeds if:

  • A beginner can explain the system back to you
  • The user knows what actions increase/decrease results
  • The user understands why each major piece exists (not just what it does)

© kv0906, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/explain of kv0906/pm-kit.

Open the folder on GitHubat commit 2cb5d9f

Compare with similar skills

Explain 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.

Explain compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Explain this skillkv0906/pm-kit138—~941Automated safety check: PassMIT
Concept Explaineraipoch/medical-research-skills2k—~1.9kAutomated safety check: PassMIT
Mathparcadei/Continuous-Claude-v33.9k3 repos~1.6kAutomated safety check: NotesMIT
Plain-Language Concept Explainerlijigang/ljg-skills7.5k—~632Automated safety check: PassMIT
Math Computationtradecatlabs/vibe-coding-cn17k—~881Automated safety check: PassMIT
Concept Explainerchmonitor/chmonitor299—~2.1kAutomated safety check: PassGPL-3.0

Similar skills

  • Concept Explainer

    aipoch/medical-research-skills

    Uses analogies to explain complex medical concepts in accessible terms.

    2k GitHub stars~1.9k tokensUpdated 21 days ago
    EducationAuto-check passed

  • Math

    parcadei/Continuous-Claude-v3

    Unified math capabilities - computation, solving, and explanation.

    3.9k GitHub starsUsed in 3 repos~1.6k tokens
    Research & ScienceAuto-check: notes

  • Plain-Language Concept Explainer

    lijigang/ljg-skills

    Explains a concept, formula or mechanism in plain Chinese so the reader can recognize it, follow the reasoning, adjust it when conditions change and apply it to new cases.

    7.5k GitHub stars~632 tokensUpdated yesterday
    EducationAuto-check passed

  • Math Computation

    tradecatlabs/vibe-coding-cn

    Runs reproducible math computations and counterexample searches with SymPy, NumPy and mpmath, logging evidence without presenting results as proofs.

    17k GitHub stars~881 tokensUpdated today
    Research & ScienceAuto-check passed

  • Concept Explainer

    chmonitor/chmonitor

    Explains core ClickHouse concepts with accurate mental models — MergeTree, indexes, replication, sharding, and special engines.

    299 GitHub stars~2.1k tokensUpdated 2 days ago
    DatabasesAuto-check passed

  • Explain Like Socrates

    sickn33/agentic-awesome-skills

    Explains concepts using Socratic-style dialogue. An agent skill from sickn33/agentic-awesome-skills.

    47k GitHub starsUsed in 2 repos~1.2k tokens
    EducationAuto-check passed

More from kv0906/pm-kit

All 26 skills in this repo

  • Mermaid Visualizer

    kv0906/pm-kit

    Transform text content into professional Mermaid diagrams for presentations and documentation.

    138 GitHub starsUsed in 2 repos~2.2k tokens
    Auto-check passed

  • Gws

    kv0906/pm-kit

    This skill should be used when the user asks to "set up gws", "install Google Workspace CLI", "connect Gmail to Claude", "manage Google Drive from terminal", "send email from CLI", "check my…

    138 GitHub stars~1.6k tokensUpdated 3 mo ago
    Auto-check passed

  • Jira

    kv0906/pm-kit

    Jira integration via acli CLI. An agent skill from kv0906/pm-kit.

    138 GitHub stars~4.2k tokensUpdated 3 mo ago
    Auto-check: notes

  • Excalidraw Generator

    kv0906/pm-kit

    Professional Excalidraw diagram generation expert that creates complete, valid .excalidraw.json files based on user descriptions.

    138 GitHub stars~3k tokensUpdated 3 mo ago
    Auto-check passed

  • Ask

    kv0906/pm-kit

    Fast vault Q&A — quick lookups, decision history, blocker status, doc search.

    138 GitHub stars~781 tokensUpdated 3 mo ago
    Auto-check passed

  • Block

    kv0906/pm-kit

    Flag a blocker with severity, owner, and due date. An agent skill from kv0906/pm-kit.

    138 GitHub stars~466 tokensUpdated 3 mo ago
    Auto-check: notes

Questions about Explain

What does Explain do?

Break down complex concepts (math, models, systems, terminology) into first-principles explanations. Explain is an agent skill from kv0906/pm-kit. Break down complex concepts (math, models, systems, terminology) into first-principles explanations.

When should I use Explain?

Explain fits situations like: user says explain; break this down; first principles; pastes a formula/model/system to understand.

How do I install Explain in Claude Code?

Run `npx skills add kv0906/pm-kit --skill explain -a claude-code`. Or copy the skill folder (.claude/skills/explain in kv0906/pm-kit) into .claude/skills/explain in your project. Claude Code loads it when a task matches its description.

How do I install Explain in Codex?

Run `npx skills add kv0906/pm-kit --skill explain -a codex`. Or copy the skill folder (.claude/skills/explain in kv0906/pm-kit) into .agents/skills/explain in your project. Codex loads it when a task matches its description.

Can I use Explain 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 kv0906/pm-kit --skill explain -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/explain, .gemini/skills/explain, .github/skills/explain and .opencode/skills/explain in your project.

What does Explain need to run?

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

Does Explain 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 Explain 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 Explain use?

Explain is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Explain use?

About 941 tokens (SKILL.md is roughly 3.8k 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 Explain?

Skills that share tags, products or a category with Explain: Concept Explainer (aipoch/medical-research-skills, 2k stars), Math (parcadei/Continuous-Claude-v3, 3.9k stars), Plain-Language Concept Explainer (lijigang/ljg-skills, 7.5k stars) and Math Computation (tradecatlabs/vibe-coding-cn, 17k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Explain?

kv0906 (a GitHub user) maintains it in kv0906/pm-kit, which has 138 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on June 29, 2026.

Source: kv0906/pm-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.