understand-knowledge

Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.

Quality

76%

Does it follow best practices?

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Adds up to 20 points to the overall score

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Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./understand-anything-plugin/skills/understand-knowledge/SKILL.md

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is a well-sequenced, actionable workflow with strong validation and error handling. Its weakest point is progressive disclosure: it references bundled Python scripts that are not actually present in the skill bundle.

Suggestions

Ship the referenced parse-knowledge-base.py and merge-knowledge-graph.py in a scripts/ directory so the invoked commands resolve.

Provide the article-analyzer subagent prompt template verbatim (or in a referenced file) so the ANALYZE phase is fully reproducible.

Tighten the 'What It Detects' section to bullet signals only, moving the pattern definition to a reference file if more detail is needed.

Dimension	Reasoning	Score
Conciseness	The body is efficient and task-focused with tight phase descriptions and code blocks; the 'What It Detects' and 'Notes' sections add minor explanatory padding that could be trimmed but is largely justified for a niche pattern.	4 / 5
Actionability	Provides concrete, executable commands (python3 parse/merge scripts, guarded bash cleanup) and specific batching parameters, but the article-analyzer subagent prompt is described rather than given verbatim, leaving a minor gap.	4 / 5
Workflow Clarity	Five phases are clearly sequenced with explicit validation (Phase 5 step 2 checks node/edge integrity), error-recovery feedback (Phase 1 script-error handling, Phase 3 batch-failure continuation), and a guarded destructive cleanup, matching the anchor for clear sequence with explicit validation and feedback loops.	5 / 5
Progressive Disclosure	The file is well-structured with clear sections and one-level-deep script references, but the referenced bundle scripts (parse-knowledge-base.py, merge-knowledge-graph.py) are not present in the bundle, leaving those references unresolvable.	3 / 5
	Total	16 / 20 Passed

Description

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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 specific and highly distinctive within its niche, clearly stating what the skill does. Its main weakness is the absence of any explicit 'when to use it' trigger guidance, which caps completeness.

Suggestions

Add a 'Use when...' clause naming trigger phrases (e.g., 'Use when the user wants a knowledge graph from a wiki, or mentions Karpathy-pattern wiki, index.md, or wikilinks').

Include common synonyms or file/structure markers (e.g., 'index.md', 'log.md', wikilinks') to broaden natural trigger coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'analyze a...knowledge base', 'generate an interactive knowledge graph', 'entity extraction, implicit relationships, and topic clustering' — giving comprehensive coverage of the skill's capabilities, matching the anchor for several specific concrete actions.	5 / 5
Completeness	Provides a clear 'what' (analyze wiki, generate knowledge graph) but no 'Use when...' clause or equivalent trigger guidance, so per the judging guideline completeness is capped at 3.	3 / 5
Trigger Term Quality	Contains good natural keywords ('knowledge graph', 'knowledge base', 'entity extraction', 'topic clustering', 'wiki') a user might say, but lacks common synonyms or file extensions, sitting above the 'some relevant keywords' anchor but short of comprehensive coverage.	4 / 5
Distinctiveness Conflict Risk	The 'Karpathy-pattern LLM wiki' framing carves a clear, narrow niche with distinct triggers and minimal overlap risk with other skills.	5 / 5
	Total	17 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: Egonex-AI/Understand-Anything
Path: understand-anything-plugin/skills/understand-knowledge/SKILL.md
Commit: ba450c4

Reviewed: ~16 hours ago

Table of Contents

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