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Understand Diff

OrganizationPopular
Egonex-AI
understand-diff

Use when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks

Overview

PublisherEgonex-AI
RepositoryUnderstand-Anything
Skill nameunderstand-diff
Stars
83.2K
Forks
7K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Egonex-AI on GitHub. Read the source before you install it.

Installation

Install the Understand Diff AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Egonex-AI/Understand-Anything.git /tmp/Understand-Anything
mkdir -p .claude/skills
cp -r /tmp/Understand-Anything/understand-anything-plugin/skills/understand-diff .claude/skills/understand-diff
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Understand Diff in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Understand Diff on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Understand Diff is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/understand-diff

Analyze the current code changes against the knowledge graph in the project's data directory (.ua/knowledge-graph.json, or the legacy .understand-anything/knowledge-graph.json when that directory is present).

Graph Structure Reference

The knowledge graph JSON has this structure:

  • project — {name, description, languages, frameworks, analyzedAt, gitCommitHash}
  • nodes[] — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}
    • Code node types: file, function, class, module, concept
    • Non-code node types: config, document, service, table, endpoint, pipeline, schema, resource
    • Domain/knowledge node types: domain, flow, step, article, entity, topic, claim, source
    • IDs use the node type as prefix, e.g. file:path, function:path:name, config:path, article:path
  • edges[] — each has {source, target, type, direction, weight}
    • Key types: imports, contains, calls, depends_on, configures, documents, deploys, triggers, contains_flow, flow_step, related, cites
  • layers[] — each has {id, name, description, nodeIds[]}
  • tour[] — each has {order, title, description, nodeIds[]}

How to Read Efficiently

  1. Use Grep to search within the JSON for relevant entries BEFORE reading the full file
  2. Only read sections you need — don't dump the entire graph into context
  3. Node names and summaries are the most useful fields for understanding
  4. Edges tell you how components connect — follow imports and calls for dependency chains

Instructions

  1. Resolve the data directory $UA_DIR. Run UA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua) — this is the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Check that $UA_DIR/knowledge-graph.json exists. If not, tell the user to run /understand first.

  2. Get the changed files list (do NOT read the graph yet):

    • If on a branch with uncommitted changes: git diff --name-only
    • If on a feature branch: git diff main...HEAD --name-only (or the base branch)
    • If the user specifies a PR number: get the diff from that PR
  3. Read project metadata and check graph freshness — use Grep or Read with a line limit to extract the "project" section, including gitCommitHash as GRAPH_COMMIT_RAW, then:

    • Resolve it as a commit before using it in any Git diff. From the project root, compare the resolved commit with git rev-parse HEAD and inspect project-scoped committed and working-tree changes:
      bash
      GRAPH_COMMIT=$(git rev-parse --verify --end-of-options "${GRAPH_COMMIT_RAW}^{commit}" 2>/dev/null)
      git rev-parse HEAD
      git diff --name-only "$GRAPH_COMMIT" HEAD -- .
      git diff --cached --name-only -- .
      git diff --name-only -- .
      git ls-files --others --exclude-standard -- .
    • The -- . pathspec is required: commits that only touch a sibling monorepo project must not make this graph stale. A hash mismatch alone is not stale when the project diff is empty.
    • Ignore the selected data directory (.ua/ or legacy .understand-anything/) in every command's output because it contains generated graph artifacts, not project source drift.
    • If the committed diff or any working-tree command reports project files, warn before impact analysis that the graph may omit those changes. Suggest: Run /understand to refresh the graph.
    • Run the commit diff only when GRAPH_COMMIT_RAW resolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.
  4. Find nodes for changed files — for each changed file path, use Grep to search the knowledge graph for:

    • Nodes with matching "filePath" values (e.g., grep "changed/file/path")
    • This finds file-level nodes (including non-code types) AND function/class nodes defined in those files
    • Note the id values of all matched nodes
  5. Find connected edges (1-hop) — for each matched node ID, Grep for that ID in the edges to find:

    • What imports or depends on the changed nodes (upstream callers)
    • What the changed nodes import or call (downstream dependencies)
    • These are the "affected components" — things that might break or need updating
  6. Identify affected layers — Grep for the matched node IDs in the "layers" section to determine which architectural layers are touched.

  7. Provide structured analysis:

    • Changed Components: What was directly modified (with summaries from matched nodes)
    • Affected Components: What might be impacted (from 1-hop edges)
    • Affected Layers: Which architectural layers are touched and cross-layer concerns
    • Risk Assessment: Based on node complexity values, number of cross-layer edges, and blast radius (number of affected components)
    • Suggest what to review carefully and any potential issues
  8. Write diff overlay for dashboard — after producing the analysis, write the diff data to $UA_DIR/diff-overlay.json so the dashboard can visualize changed and affected components. The file contains:

    json
    {
      "version": "1.0.0",
      "baseBranch": "<the base branch used>",
      "generatedAt": "<ISO timestamp>",
      "changedFiles": ["<list of changed file paths>"],
      "changedNodeIds": ["<node IDs from step 4>"],
      "affectedNodeIds": ["<node IDs from step 5, excluding changedNodeIds>"]
    }

    After writing, tell the user they can run /understand-anything:understand-dashboard to see the diff overlay visually.

Frequently asked questions

What does the Understand Diff AI skill do?

Use when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks

Why use Understand Diff on TypingMind?

Because you install it once and use it with any model. Understand Diff is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Understand Diff in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Egonex-AI/Understand-Anything/tree/main/understand-anything-plugin/skills/understand-diff. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Understand Diff?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Understand Diff?

As many as you like. As long as a model supports skills, you can use Understand Diff with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Understand Diff AI skill free?

Yes. It is published on GitHub by Egonex-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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