Content
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is highly actionable and excellently structured for progressive disclosure, with real, verified reference paths and concrete commands throughout. Its main weakness is conciseness (repeated rule restatements and a duplicated script block) and the absence of explicit validation feedback loops for the batch build/regeneration operations.
Suggestions
Remove the duplicated initialization script block — reference 'Updating References' from INITIALIZATION instead of repeating the three commands verbatim in both sections.
Consolidate the 'NEVER use absolute values' guidance so the rule, the reverse-lookup steps, and the token-priority list are stated once rather than restated across three sections and a table.
Add an explicit validate/retry checkpoint to the build and reference-regeneration workflows (e.g., after running the scripts, verify references/component-index.md and token-map.md exist and are non-empty before proceeding).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is largely lean and assumes Claude's competence (no concept explanations of what design systems are), but it carries genuine repetition: the initialization script block appears twice (INITIALIZATION and Updating References) and the 'NEVER use absolute values' rule is restated across the CRITICAL RULE list, the 'When encountering absolute values' steps, the 'Token usage priority' list, and the reference table. This matches 'mostly efficient but could be tightened'. Not level 3 because the redundancy means not every token earns its place. | 2 / 3 |
Actionability | Provides fully executable, copy-paste-ready guidance throughout: concrete commands ('npm info @gitlab/ui peerDependencies --json', 'bash scripts/update-refs.sh'), real import statements ('import { GlButton, GlCheckbox, GlAvatar } from \'@gitlab/ui\''), specific token names ('var(--gl-color-blue-500)', 'gl-p-3'), and exact reference file paths. Clearly above level 2's pseudocode/incomplete anchor. | 3 / 3 |
Workflow Clarity | Multi-step processes are well sequenced (numbered Component Lookup Workflow 1-4, Figma lookup chain 1-5 with an 'Ask the user' fallback, scaffold with a 'Verify after install' checkpoint), but the batch build/regeneration operations (INITIALIZATION scripts, Updating References) and the destructive token-replacement work lack explicit validate-then-retry feedback loops. Per the rubric's destructive/batch note, missing feedback loops caps this at 2. | 2 / 3 |
Progressive Disclosure | SKILL.md is a well-organized overview with clearly signaled, one-level-deep references to real bundle paths (references/component-index.md, references/design-tokens/token-map.md, references/pajamas-docs/{components,patterns,...}/). The referenced files are confirmed real: build-index.py generates component-index.md, build-token-map.py generates token-map.md, and update-refs.sh creates the references/pajamas-docs/ and references/design-tokens/source/{constant,semantic,contextual} structure. Content is appropriately split with navigation tables. | 3 / 3 |
Total | 10 / 12 Passed |