tracing-upstream-lineage
Trace upstream data lineage. Use when the user asks where data comes from, what feeds a table, upstream dependencies, data sources, or needs to understand data origins.
84
80%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/tracing-upstream-lineage/SKILL.mdQuality
Discovery
89%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 well-structured description with excellent trigger terms and completeness, clearly answering both what the skill does and when to use it. Its main weakness is that the 'what' portion is somewhat thin—it names only one action ('trace upstream data lineage') rather than elaborating on specific capabilities like column-level tracing, dependency graph generation, or source identification. Overall, it would perform well in skill selection scenarios.
Suggestions
Expand the capability description with more specific actions, e.g., 'Trace upstream data lineage, identify source tables and columns, map dependency chains, and visualize data flow paths.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain (data lineage) and a core action ('trace upstream data lineage'), but it only describes one action rather than listing multiple specific concrete actions (e.g., visualize dependency graphs, list source tables, trace column-level lineage). | 2 / 3 |
Completeness | Clearly answers both 'what' (trace upstream data lineage) and 'when' (explicit 'Use when...' clause listing multiple trigger scenarios like asking about data sources, upstream dependencies, and data origins). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would actually say: 'where data comes from', 'what feeds a table', 'upstream dependencies', 'data sources', 'data origins'. These cover multiple natural phrasings a user might use. | 3 / 3 |
Distinctiveness Conflict Risk | The focus on 'upstream data lineage' is a clear niche with distinct triggers. Terms like 'upstream dependencies', 'what feeds a table', and 'data origins' are specific enough to avoid conflicts with general data processing or querying skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
70%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill with a clear multi-step workflow for tracing upstream data lineage. Its strengths are the logical step sequence, good use of cross-references to related skills, and concrete CLI commands. Its weaknesses are moderate verbosity in the output template section and examples that are more illustrative than fully executable.
Suggestions
Trim the Output: Lineage Report section—Claude can generate appropriate report formats without a full template; focus on specifying what information to include rather than exact formatting.
Make the CLI examples more concrete and executable, e.g., show a complete command sequence with expected output patterns rather than just listing command names.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient but includes some unnecessary elaboration. The 'On Astro' and 'On OSS Airflow' sections are brief but could be tighter. The output template section is quite lengthy with the report format, table template, and quality implications—some of which Claude could infer. However, it avoids explaining basic concepts like what Airflow is. | 2 / 3 |
Actionability | Provides concrete CLI commands (af dags list, af dags source, af tasks list, af dags stats) and SQL pattern examples, which is good. However, the code examples are illustrative rather than fully executable—the SQL snippets and lineage diagrams are templates/pseudocode rather than copy-paste ready commands. The investigation steps are clear but somewhat abstract in places. | 2 / 3 |
Workflow Clarity | The 5-step workflow is clearly sequenced and logical: identify target → find producing DAG → trace sources → build lineage chain → check source health. The recursive tracing in Step 4 is well-illustrated with the ASCII diagram. Step 5 includes a validation/health check step. The column-level lineage section adds a clear sub-workflow. The process naturally builds on each step. | 3 / 3 |
Progressive Disclosure | The content is well-structured with clear sections and headers. It appropriately references other skills (checking-freshness, debugging-dags, tracing-downstream-lineage, etc.) as one-level-deep pointers rather than inlining their content. The main workflow, column-specific lineage, and output template are logically separated. For a skill of this complexity, the organization is effective. | 3 / 3 |
Total | 10 / 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
166c98a
- Reviewed
Table of Contents
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