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understand-chat

Use when you need to ask questions about a codebase or understand code using a knowledge graph

Install / Use

npx skills add Egonex-AI/Understand-Anything --skill understand-chat

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

87/100

Supported Platforms

Zed

Our assessment of understand-chat

understand-chat scores 87/100 on our quality scale, 395th of 1,751 Development & Engineering skills we index (top 23%).

Its SKILL.md is 4.6 KB long, split into 4 sections and no code examples: a solid amount of guidance for an agent.

With 84,018 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
8/20
Description
12/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 13 days ago, so understand-chat is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

understand-chat compared with similar skills

All 4 of these similar skills score higher than understand-chat; compare them before choosing.

SkillScoreStarsUpdatedFormat
understand-chat (this skill)by Egonex-AI8784.0k13d agoSKILL.md
Agent-Reachby Panniantong10085.4k9d agoCLAUDE.md
ai-job-searchby MadsLorentzen10043.9k4d agoCLAUDE.md
claude-howtoby luongnv8910041.7k5d agoCLAUDE.md
algorithmic-artby anthropics100177.9k2d agoSKILL.md

Frequently asked questions

How do I install understand-chat?
Run npx skills add Egonex-AI/Understand-Anything --skill understand-chat. The install tabs above show the steps for each supported agent.
Which AI agents does understand-chat work with?
It is written for Zed, as a SKILL.md file. Other agents that read the same format can often use it too.
Is understand-chat safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is understand-chat still maintained?
The repository was last updated 13 days ago, so understand-chat is actively maintained.

name: understand-chat description: Use when you need to ask questions about a codebase or understand code using a knowledge graph argument-hint: "[query]"

/understand-chat

Answer questions about this codebase using 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 in the current project root. If not, tell the user to run /understand first.

  2. Check graph freshness before using graph-derived context:

    • Read project.gitCommitHash from the graph metadata as GRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it with git rev-parse HEAD and inspect project-scoped committed and working-tree changes from the project root:
      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 answering that graph-derived context 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.
  3. Read project metadata only — use Grep or Read with a line limit to extract just the "project" section from the top of the file for context (name, description, languages, frameworks).

  4. Search for relevant nodes — use Grep to search the knowledge graph file for the user's query keywords: "$ARGUMENTS"

    • Search "name" fields: grep -i "query_keyword" in the graph file
    • Search "summary" fields for semantic matches
    • Search "tags" arrays for topic matches
    • Note the id values of all matching nodes
  5. Find connected edges — for each matched node ID, Grep for that ID in the edges section to find:

    • What it imports or depends on (downstream)
    • What calls or imports it (upstream)
    • This gives you the 1-hop subgraph around the query
  6. Read layer context — Grep for "layers" to understand which architectural layers the matched nodes belong to.

  7. Answer the query using only the relevant subgraph:

    • Reference specific files, functions, and relationships from the graph
    • Explain which layer(s) are relevant and why
    • Be concise but thorough — link concepts to actual code locations
    • If the query doesn't match any nodes, say so and suggest related terms from the graph

Related Skills

View on GitHub
GitHub Stars84.0k
CategoryDevelopment
Updated13d ago
Forks7.1k

Languages

TypeScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions