Provisions and manages Neo4j Aura instances via CLI (aura-cli v1.7+) or REST API. Use when creating, pausing, resuming, resizing, or deleting AuraDB Free/Professional/Business Critical/VDC instances; downloading credentials; scripting CI/CD pipelines; polling async status; or using the Terraform neo4j/neo4j-aura provider. Covers auth setup (client credentials OAuth2), credential lifecycle (download once — never recoverable), instance type selection, region codes, and Python provisioning scripts. Does NOT handle Cypher queries — use neo4j-cypher-skill. Does NOT cover Graph Data Science algorithms — use neo4j-gds-skill or neo4j-aura-graph-analytics-skill. Does NOT cover neo4j-admin/cypher-shell — use neo4j-cli-tools-skill.
91
88%
Does it follow best practices?
Impact
99%
1.37xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
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 an excellent skill description that thoroughly covers specific capabilities, includes rich natural trigger terms, explicitly states both what the skill does and when to use it, and proactively delineates boundaries with related skills. The negative boundary clauses ('Does NOT handle...use X-skill') are particularly effective for disambiguation in a multi-skill environment. The description is detailed without being padded, and uses proper third-person voice throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: provisioning, managing, creating, pausing, resuming, resizing, deleting instances, downloading credentials, scripting CI/CD pipelines, polling async status, auth setup, credential lifecycle, instance type selection, region codes, and Python provisioning scripts. | 3 / 3 |
Completeness | Clearly answers both 'what' (provisions and manages Neo4j Aura instances via CLI or REST API, covers auth setup, credential lifecycle, etc.) and 'when' (explicit 'Use when' clause listing creating, pausing, resuming, resizing, deleting instances, downloading credentials, scripting CI/CD pipelines, polling async status, or using Terraform provider). Additionally includes explicit negative boundaries directing to other skills. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Neo4j Aura', 'aura-cli', 'AuraDB', 'Free/Professional/Business Critical/VDC', 'credentials', 'CI/CD', 'Terraform', 'neo4j-aura provider', 'OAuth2', 'REST API', 'pausing', 'resuming', 'resizing'. These are terms a user working with Neo4j Aura would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with explicit boundary definitions using 'Does NOT handle' clauses that redirect to specific other skills (neo4j-cypher-skill, neo4j-gds-skill, neo4j-aura-graph-analytics-skill, neo4j-cli-tools-skill). The niche of Neo4j Aura instance provisioning and management is clearly carved out and unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality, highly actionable skill that provides comprehensive coverage of Neo4j Aura provisioning across CLI, REST API, Python, and Terraform. Its main weakness is length — the region tables, full Python script, and Terraform config inflate the file significantly and would benefit from being split into bundle files. The workflow is exceptionally clear with explicit validation checkpoints, credential safety warnings, and error recovery guidance.
Suggestions
Extract region code tables into a separate REGIONS.md bundle file and reference it from the main skill to reduce token footprint by ~60 lines.
Move the full Python CI/CD provisioning script into a bundle file (e.g., scripts/provision.py or PYTHON_PROVISIONING.md) and keep only a brief summary with a reference in the main SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is mostly efficient with good use of tables and code blocks, but the region code tables (~60 lines), the full Python provisioning script, and the Terraform block make it quite long. Some of this reference material (regions, full Python script) could be split into bundle files. However, it avoids explaining basic concepts Claude already knows. | 2 / 3 |
Actionability | Excellent actionability throughout — every operation has fully executable CLI commands, REST API curl calls, and a complete Python script. Code is copy-paste ready with proper variable substitution, and the field reference tables provide all required parameters. | 3 / 3 |
Workflow Clarity | The numbered step sequence (List Tenants → Create → Poll → Write .env → Lifecycle Ops) is clear and well-ordered. Critical validation checkpoints are explicit: polling for status before proceeding, credential capture warnings in bold, state preconditions for each lifecycle operation, and the poll_status function includes timeout and error handling with a feedback loop. | 3 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and a logical flow, but it's a monolithic ~350-line file with no bundle files. The region tables, Python CI/CD script, Terraform config, and error reference table could all be split into separate referenced files to keep the main SKILL.md leaner. The WebFetch URLs section is a good touch for external references. | 2 / 3 |
Total | 10 / 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 | |
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Table of Contents
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