agentleFS
Sign inStart free
GrishaAngelovGHGrishaAngelovGH/gemini-cli-agent-skills/project-feature-explainer/SKILL.md

project-feature-explainer

Skill16 starsChanged 10 months agoMITView on GitHub

Expert guidance for explaining project features. Use this skill when you need to provide a comprehensive explanation of how a specific feature works, including summaries, deep dives, usage examples, and sequence/workflow diagrams. This skill has references directory which contains additional instructions `checklist.md`, `example-output.md` and `explanation-template.md` that MUST be used for every analysis.

The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Reference Code: Use specific file paths and symbol names.

    line 36

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “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

Project Feature Explainer Skill

This skill provides a systematic approach to analyzing and explaining a specific feature within a codebase.

Workflow

  1. Identify Entry Points: Locate the main functions, classes, or API endpoints that trigger the feature.
  2. Trace Dependencies: Identify the internal modules, services, or external APIs the feature relies on.
  3. Analyze Data Flow: Understand how data enters the feature, how it's transformed, and where it's stored or returned.
  4. Draft Explanation: Structure the explanation using the mandatory sections below.
  5. Verify: Cross-reference the draft with the references/checklist.md to ensure completeness.

Mandatory Output Structure

1. Feature Summary

A high-level overview (1-2 paragraphs) explaining what the feature does and why it exists.

2. Deep Dive (Technical Details)

A detailed breakdown of the internal implementation.

  • Key Components: List the main files/classes/functions involved.
  • Logic Flow: Step-by-step description of the execution path.
  • State Changes: Describe any side effects (e.g., database updates, cache invalidation).

3. Usage & Examples

Code snippets or CLI commands showing how to use the feature.

  • Include common parameters and expected outputs.
  • Provide a "Happy Path" example.

Guidelines

  • Be Concise: Focus on the "how" and "why" without repeating obvious code logic.
  • Reference Code: Use specific file paths and symbol names.
  • Contextualize: Explain how this feature fits into the broader system architecture.

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