agentleFS
Sign inStart free
tykisgodtykisgod/quick-question/skills/explain/SKILL.md

explain

Skill12 starsChanged 8 months agoMITView on GitHub

Explain the architecture and logic of a specified module or design in plain, approachable language.

122 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use debug-fix, root-cause and 9 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • zebbernSkill

    debug-fix

    Find and fix a bug or issue — from any source (GitHub issue, error message, user report, or observed behavior)

    Also in 3 projects that use this

  • Ingramradical235Skill

    root-cause

    Structured root cause analysis using WHERE (MECE decomposition) then WHY (causal structure diagrams) pipeline. Includes coin-flip detection, logical-leap detection, and vicious cycle intervention. Use when buffer enters YELLOW/RED, when metrics stall, or when Actions execute but don't produce results.

    Also in 5 projects that use this

  • ralphkraussSkill

    resolve-conflicts

    Resolve git merge conflicts or re-apply changes from a stale branch onto current main. Use when user says "resolve conflicts", "merge conflicts", "rebase branch", "branch is behind", "re-apply changes", "port branch", or a branch is too far behind main to merge cleanly.

    Also in 4 projects that use this

  • neurofooSkill

    socratic

    Socratic questioning to examine beliefs, uncover assumptions, and develop deeper understanding. Use to challenge thinking, evaluate proposals, or teach without lecturing.

    Also in 4 projects that use this

  • anombyte93Skill

    discover

    Phase 1 of the prd-taskmaster pipeline: brainstorm-driven discovery. Delegates to superpowers:brainstorming in Interactive Mode (one adaptive question at a time), or self-brainstorms in Autonomous Mode when no user is present. Intercepts before the brainstorming chain hands off to writing-plans — this skill owns the exit. Extracts constraints, calibrates scale (Solo / Team / Enterprise), and advances the pipeline to GENERATE.

    Also in 6 projects that use this

  • mitsuhikoSkill

    summarize

    Fetch a URL or convert a local file (PDF/DOCX/HTML/etc.) into Markdown using `uvx markitdown`, optionally it can summarize

    Also in 8 projects that use this

The file

We split this skill into the rules it gives an agent

6 rules. 0 are common, 5 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 109 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read design docs: Start by checking for project documentation (e.g., Docs/, Documentation/, or AGENTS.md) to understand the design intent

    line 14
  2. Distinctive:

    Start with a real-world analogy to build intuition

    line 17
  3. Distinctive:

    If there is a history of evolution (changed from A to B), explain the motivation

    line 20
  4. Distinctive:

    Do not paste large blocks of source code.

    line 23
  5. Distinctive:

    Do not pile on design pattern terminology (say "each ship has its own service container", not "per-instance service locator pattern with …

    line 24
  6. Distinctive:

    Do not assume the reader knows the project history

    line 25

“Common” is measured: kept by at least 6 in 10 of the 109 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Respond in the user's preferred language (detect from their recent messages, or fall back to the language setting in CLAUDE.md).

In a Unity project, for "how does X work right now", also query the live Editor (read-only) so you explain what the code actually does, not just what it says. Channel per shared/unity-live-state.md: official Unity CLI (Library/Pipeline/.unity-pipeline-port exists; never open or print it — it holds an eval token) → unity command --project-path "$PWD" --json --no-banner <find_gameobjects|get_component_properties|get_serialized_fields|get_scene_hierarchy> -- <params> (parameters: unity command --project-path "$PWD" --query <keyword> --detail full --json); tykit (Temp/tykit.json) → get-properties / get-field / get-array / inspect; neither → explain from source and say the runtime values are unverified.

Arguments: $ARGUMENTS

  • Module or design name (e.g., "PlayerController", "inventory system", "save system")

Behavior

  1. Read design docs: Start by checking for project documentation (e.g., Docs/, Documentation/, or AGENTS.md) to understand the design intent
  2. Read core code: Find the key interfaces and implementation classes to understand the actual structure
  3. Explain in plain language, following these principles:
    • Start with a real-world analogy to build intuition
    • Then break down the concrete code structure (use a tree diagram or simple illustration)
    • Explain "why it was designed this way" not just "what it is"
    • If there is a history of evolution (changed from A to B), explain the motivation
    • Point out common pitfalls or misconceptions
  4. Do not:
    • Do not paste large blocks of source code; use pseudocode or key lines instead
    • Do not pile on design pattern terminology (say "each ship has its own service container", not "per-instance service locator pattern with dependency injection")
    • Do not assume the reader knows the project history

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free