understand-chat
Use when you need to ask questions about a codebase or understand code using a knowledge graph
46
48%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./understand-anything-plugin/skills/understand-chat/SKILL.mdQuality
Discovery
40%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description is too vague about what the skill actually does — it lacks concrete actions and specific capabilities. While it includes a 'Use when' clause and the term 'knowledge graph' provides some distinctiveness, the overall description would struggle to help Claude differentiate this skill from other code analysis or understanding tools.
Suggestions
Add specific concrete actions the skill performs, e.g., 'Queries a code knowledge graph to trace function call chains, identify dependencies, map class hierarchies, and find symbol references across a codebase.'
Expand trigger terms to include natural user phrases like 'code structure', 'dependencies', 'call graph', 'code navigation', 'how does this function work', 'where is this used'.
Clarify what makes this distinct from general code reading — emphasize the knowledge graph aspect, e.g., 'Uses a pre-built knowledge graph for structural queries rather than raw text search.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses vague language like 'ask questions about a codebase' and 'understand code' without listing any concrete actions. It doesn't specify what kinds of questions, what aspects of understanding, or what outputs are produced. | 1 / 3 |
Completeness | It has a 'Use when' clause addressing when to use it, but the 'what does this do' part is extremely weak — it only vaguely says 'ask questions' and 'understand code' without describing concrete capabilities or outputs. | 2 / 3 |
Trigger Term Quality | It includes some relevant terms like 'codebase', 'understand code', and 'knowledge graph' that users might mention, but misses common variations like 'code analysis', 'code search', 'code navigation', 'code structure', or 'code relationships'. | 2 / 3 |
Distinctiveness Conflict Risk | 'Knowledge graph' provides some distinctiveness, but 'ask questions about a codebase' and 'understand code' are very broad and could easily overlap with general code analysis, code search, or code review skills. | 2 / 3 |
Total | 7 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a solid framework for querying a knowledge graph with a clear workflow and useful structural reference. Its main weaknesses are the lack of concrete, executable grep/jq commands (relying on vague descriptions instead) and missing error handling or validation checkpoints in the workflow. The graph structure reference is a valuable addition but could be slightly more concise.
Suggestions
Replace vague grep descriptions with concrete, executable commands — e.g., `grep -n '"name":.*"auth"' .understand-anything/knowledge-graph.json` — so Claude can copy-paste them directly.
Add error handling guidance: what to do when grep returns 0 results, too many results (>50 matches), or when the JSON file is very large (e.g., use `jq` for structured queries instead of grep).
Trim the exhaustive node type listings — group them or just list the most common ones, noting 'and other domain-specific types' to save tokens.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The graph structure reference section is useful and mostly efficient, but some parts are slightly verbose — e.g., listing all node types exhaustively when Claude could infer many. The 'How to Read Efficiently' section adds value but tip #3 is somewhat obvious for Claude. | 2 / 3 |
Actionability | The instructions provide a clear sequence of grep-based searches but lack concrete, executable commands — e.g., actual grep command syntax with proper flags and patterns for searching JSON. The '$ARGUMENTS' placeholder is good but the grep examples are vague ('grep -i "query_keyword"') rather than copy-paste ready with proper file paths and jq/grep patterns. | 2 / 3 |
Workflow Clarity | The 6-step workflow is clearly sequenced and logical, with a good initial validation check (step 1). However, there are no explicit validation checkpoints or error recovery steps — e.g., what to do if grep returns too many results, if the JSON is malformed, or if no nodes match. The fallback in step 6 ('say so and suggest related terms') is minimal. | 2 / 3 |
Progressive Disclosure | For a skill of this size (~50 lines) with no need for external references, the content is well-organized into clear sections: graph structure reference, reading tips, and step-by-step instructions. The structure is appropriate and easy to navigate without needing additional files. | 3 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- Lum1104/Understand-Anything
- Commit
26edf61
- Reviewed
Table of Contents
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