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understand

Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships

Quality

74%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

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tessl review fix ./understand-anything-plugin/skills/understand/SKILL.md
SKILL.md
Quality
Evals
Security

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 body delivers an exceptionally actionable, well-gated multi-phase workflow with strong validation and error-recovery loops throughout. Its main weaknesses are token efficiency and organization: a 931-line monolith that inlines schema references and deep validation-design prose that belong in one-level-deep reference files.

Suggestions

Move the KnowledgeGraph schema reference (node/edge type tables and edge weight conventions) and the symbol-loss validation design details into a separate reference file (e.g., references/graph-schema.md, references/symbol-loss-validation.md) linked from the relevant phases, cutting the main body substantially.

Trim the dense Phase 2 incremental-validation prose (paragraphs on source identity, scope indices, and parser adapters) down to the operational rules the executing agent needs, leaving the rationale and cross-product test matrix in the already-referenced docs/incremental/symbol-loss-validation.md.

Extract the inline Node validation script to a bundled scripts/ file invoked by path, matching the pattern used for the other bundled helpers.

DimensionReasoningScore

Conciseness

The 931-line body is mostly operational (commands, gates, templates) rather than padded with concepts Claude already knows, but it includes dense internal-design prose (e.g., the Phase 2 symbol-loss sections: "The strict parser emits versioned, scoped symbol evidence...", "Source identity is (file path, symbol kind, owner, name)") and an inlined 13-type/26-type schema reference that could be tightened or moved to a reference file. This fits "mostly efficient but could be tightened" rather than the minor-trim profile of score 4.

3 / 5

Actionability

Guidance is fully executable: exact bash invocations with arguments (e.g., "node \"<SKILL_DIR>/prepare-incremental.mjs\" \"$PROJECT_ROOT\" \"$LAST_COMMIT_HASH\""), a complete copy-paste-ready Node validation script ("Write the following Node.js script to $UA_DIR/tmp/ua-inline-validate.cjs"), filled dispatch-prompt templates, and concrete decision tables covering the common full/incremental/review paths.

5 / 5

Workflow Clarity

Phases 0 through 7 are explicitly sequenced with numbered steps, decision tables for every branch (full vs. incremental vs. review-only), gate checks ("verify each batchIndex ... has a corresponding batch-<batchIndex>.json ... on disk before proceeding"), explicit feedback loops (subagent retry once, one targeted symbol-repair retry, re-run validation after fixes), and hard STOP conditions ("If the script exits non-zero ... abort Phase 7 ... Do NOT proceed to step 3"). Validation is present for batch and destructive operations, so no cap applies.

5 / 5

Progressive Disclosure

Structure is good — clearly delineated phase sections with signaling of bundled scripts ("located next to this SKILL.md file"), plus references to agents/, languages/, frameworks/, and locales/ files. However, no bundle files are provided alongside this SKILL.md, and substantial content that clearly belongs in separate reference files is inlined: the KnowledgeGraph schema tables ("Node Types (13 total)", "Edge Types (26 total)", edge weights), the multi-paragraph symbol-loss validation design notes, and the full inline validator script. This sits between the score-3 and score-4 anchors; the heavy inlined reference material keeps it at 3.

3 / 5

Total

16

/

20

Passed

Description

61%Weight 40%Scale 1-5

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 clear and reasonably specific about what the skill produces, with mostly distinct trigger vocabulary, but it omits any explicit "when to use" guidance. Adding a "Use when..." clause with concrete trigger phrases would move it into the top tier.

Suggestions

Append an explicit trigger clause, e.g., "Use when the user asks to understand, explore, or onboard to a codebase/repo, or wants a visual map of its architecture, components, or dependencies."

Add natural synonyms users would say ("code", "repository", "repo", "explore", "project structure") to improve trigger-term coverage.

Mention the interactive dashboard output explicitly, since it is the primary user-facing deliverable and a natural trigger term.

DimensionReasoningScore

Specificity

"Analyze a codebase to produce an interactive knowledge graph" names the domain and 1-2 concrete actions within a single pipeline, but unlike the score-4 anchor it does not list several distinct actions — the rest of the sentence ("architecture, components, and relationships") describes the graph's purpose rather than additional capabilities.

3 / 5

Completeness

The description clearly answers "what" ("Analyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships") but contains no "when" — no "Use when..." clause or equivalent explicit trigger guidance, which caps this dimension at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Good keyword coverage: "codebase", "knowledge graph", "architecture", "components", and "relationships" are terms users would naturally say. A few natural terms and synonyms are missing (e.g., "repository", "repo", "code", "explore", "onboard"), so it falls short of the comprehensive score-5 anchor.

4 / 5

Distinctiveness Conflict Risk

"interactive knowledge graph" for codebase architecture analysis is a fairly distinct niche with minimal conflict risk against unrelated skills; only minor overlap risk with general code-analysis or documentation skills.

4 / 5

Total

14

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (932 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository

Egonex-AI/Understand-Anything

Path

understand-anything-plugin/skills/understand/SKILL.md

Reviewed

Table of Contents

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