analyzing-data
Queries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.
93
91%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
82%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 solid skill description with strong trigger term coverage and good completeness, explicitly addressing both what the skill does and when to use it. The main weaknesses are that the capability description could be more specific about concrete actions (e.g., generating SQL, joining tables, aggregating data) and some terms are broad enough to potentially overlap with other data-related skills.
Suggestions
Add more specific concrete actions like 'generates SQL queries, aggregates metrics, joins tables across schemas' to improve specificity beyond the general 'queries data warehouse'.
Consider narrowing or clarifying the scope to reduce overlap risk—e.g., specify the warehouse platform or distinguish from general analytics/visualization skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (data warehouse querying) and a general action (queries data warehouse, answers business questions), but doesn't list multiple specific concrete actions like 'generate SQL queries, aggregate metrics, join tables, export results'. The actions remain somewhat high-level. | 2 / 3 |
Completeness | Clearly answers both 'what' (queries data warehouse and answers business questions about data) and 'when' (handles questions requiring database/warehouse queries including specific trigger phrases). The trigger guidance is explicit and detailed. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'who uses X', 'how many Y', 'show me Z', 'find customers', 'what is the count', 'data lookups', 'metrics', 'trends', 'SQL analysis'. These closely match how users naturally phrase data questions. | 3 / 3 |
Distinctiveness Conflict Risk | While it targets data warehouse querying specifically, terms like 'data lookups', 'metrics', 'trends' could overlap with analytics/BI skills or general data analysis skills. The 'SQL analysis' and 'data warehouse' terms help distinguish it, but 'business questions about data' is broad enough to potentially conflict. | 2 / 3 |
Total | 10 / 12 Passed |
Implementation
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is an excellent skill file that is lean, actionable, and well-structured. The workflow is clearly sequenced with proper feedback loops (pattern success/failure recording), the CLI reference is comprehensive yet scannable, and advanced content is appropriately deferred to reference files. It respects Claude's intelligence throughout, never explaining obvious concepts.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Every section earns its place — no explanations of what a data warehouse is, no padding about SQL basics. The CLI reference tables are dense and scannable. The workflow is tight with no unnecessary prose. | 3 / 3 |
Actionability | Fully concrete and executable: every step includes exact CLI commands with real arguments, function signatures with return types, and specific flags. Claude can copy-paste these commands directly. | 3 / 3 |
Workflow Clarity | The 6-step workflow is clearly sequenced with explicit decision points (cache hit vs miss), feedback loops (pattern record --success/--failure), and a mandatory caching step before presenting results. The validation/feedback mechanism is well-defined. | 3 / 3 |
Progressive Disclosure | Clean overview with well-signaled one-level-deep references to discovery-warehouse.md and common-patterns.md. The main file contains the essential workflow and CLI reference while appropriately deferring detailed guides to separate files. | 3 / 3 |
Total | 12 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- astronomer/agents
- Commit
0642adb
- 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.