arcgis-performance
Optimize ArcGIS Maps SDK for JavaScript applications for speed, memory, and bundle size. Use for improving map initialization, data loading, query efficiency, large dataset handling, and view rendering performance in both 2D and 3D.
85
82%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly identifies a specific technology (ArcGIS Maps SDK for JavaScript), concrete optimization targets (speed, memory, bundle size), and explicit trigger scenarios (map initialization, data loading, query efficiency, large dataset handling, view rendering). It uses third person voice and is concise without being vague.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: optimize for speed/memory/bundle size, improve map initialization, data loading, query efficiency, large dataset handling, and view rendering performance in 2D and 3D. | 3 / 3 |
Completeness | Clearly answers both what ('Optimize ArcGIS Maps SDK for JavaScript applications for speed, memory, and bundle size') and when ('Use for improving map initialization, data loading, query efficiency, large dataset handling, and view rendering performance'). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'ArcGIS Maps SDK', 'JavaScript', 'map initialization', 'data loading', 'query efficiency', 'bundle size', 'performance', '2D and 3D', 'large dataset'. These cover the terms a developer would naturally use when seeking performance help. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — targets a specific SDK (ArcGIS Maps SDK for JavaScript) and a specific concern (performance optimization). Unlikely to conflict with general JavaScript optimization or other mapping library skills due to the explicit ArcGIS scoping. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a highly actionable skill with excellent anti-pattern/correct-pattern code examples covering the full spectrum of ArcGIS JS SDK performance optimization. Its main weaknesses are length (the document is quite long for a single SKILL.md with no external references) and the absence of validation/verification steps to confirm optimizations are working. The 'Common Pitfalls' section is largely redundant with the body content.
Suggestions
Remove or significantly condense the 'Common Pitfalls' section since it repeats guidance already covered in the body, or convert it to a brief checklist of one-liners.
Split detailed sections (Large Dataset Handling, Memory Management, 3D Scene Performance) into separate referenced files, keeping SKILL.md as a concise overview with links.
Add validation checkpoints—e.g., how to measure bundle size before/after import changes, how to check for memory leaks in DevTools, or how to profile frame rates to confirm rendering improvements.
Trim or remove 'Impact' paragraphs that state obvious consequences; keep only those that provide non-obvious quantitative guidance (like the 90% payload reduction or 2000ms vs 500ms comparison).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is well-structured and avoids explaining basic concepts Claude already knows, but it's quite long (~500 lines) with some redundancy. The 'Impact' explanations after each code block, while useful, add verbosity—many state obvious consequences that Claude could infer. The 'Common Pitfalls' section at the end largely repeats guidance already covered in the body. | 2 / 3 |
Actionability | Every recommendation includes fully executable, copy-paste-ready JavaScript code with clear anti-pattern/correct-pattern pairs. Specific imports, API methods, and configuration objects are provided rather than pseudocode or vague descriptions. | 3 / 3 |
Workflow Clarity | The content is organized by priority tiers (P0/P1/P2) which provides good sequencing of importance, and the strategy thresholds table for large datasets is excellent. However, there are no explicit validation checkpoints or feedback loops—for example, no guidance on how to verify that bundle size actually decreased after switching imports, or how to confirm memory leaks are resolved after adding cleanup. | 2 / 3 |
Progressive Disclosure | The content is well-organized with clear headers and priority sections, but it's a monolithic document with no references to external files for detailed topics. The large dataset handling, memory management, and 3D performance sections could each be separate referenced documents, keeping the SKILL.md as a concise overview. | 2 / 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 |
|---|---|---|
skill_md_line_count | SKILL.md is long (802 lines); consider splitting into references/ and linking | Warning |
Total | 10 / 11 Passed | |
- Commit
d84407b
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.