CtrlK
BlogDocsLog inGet started
Tessl Logo

analyzing-data

Queries the data warehouse with SQL and answers business questions about data. Use when answering anything that needs warehouse data - counts, metrics, trends, aggregations, joins across tables, data lookups, or ad-hoc SQL analysis (for example "who uses X", "how many Y", "show me Z", "find customers", "what is the count").

76

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

92%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is concise, highly actionable, and clearly sequenced, with tool-specific operational details that justify their tokens. The main weakness is progressive disclosure: the two referenced markdown files are missing from the bundle, leaving broken links.

Suggestions

Create the referenced files (reference/discovery-warehouse.md and reference/common-patterns.md) or remove the broken links so cited paths resolve.

Consider moving the detailed CLI Reference section into a separate reference file to keep SKILL.md as a tighter overview, leaving only the core workflow and kernel functions inline.

Add a brief verification checkpoint before 'Present findings' (e.g. sanity-check row counts / nulls) to make the feedback loop explicit for query results.

DimensionReasoningScore

Conciseness

The body is lean and operational — workflow steps, a kernel-function table, and a CLI reference — with explanatory prose limited to tool-specific behavior (fail-fast, timeouts, idle kernel) that Claude would not already know, so every token earns its place.

3 / 3

Actionability

Provides fully executable, copy-paste-ready `uv run scripts/cli.py ...` commands and concrete kernel function signatures (e.g. `run_sql(query, limit=100)`), matching the top anchor for executable guidance.

3 / 3

Workflow Clarity

A clear 6-step numbered sequence (pattern lookup → concept lookup → table discovery → execute → cache → present) with a feedback checkpoint via `pattern record --success/--failure`; the operations are read-only queries so the absence of a hard validation gate is acceptable.

3 / 3

Progressive Disclosure

Sections are well organized and references are clearly signaled one level deep, but the two cited paths (reference/discovery-warehouse.md, reference/common-patterns.md) do not exist on disk, so navigation is broken and it falls short of the top anchor.

2 / 3

Total

11

/

12

Passed

Description

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.

The description is specific, third-person, and clearly states both capabilities and trigger conditions with natural user phrasings. It is concise without padding and clearly differentiated from other skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Queries the data warehouse with SQL", "counts, metrics, trends, aggregations, joins across tables, data lookups, or ad-hoc SQL analysis" — matching the top anchor for specific concrete actions.

3 / 3

Completeness

Explicitly answers what (queries the warehouse with SQL, answers business questions) and when ("Use when answering anything that needs warehouse data..."), satisfying the top anchor with an explicit trigger clause.

3 / 3

Trigger Term Quality

Includes natural user phrasings ("who uses X", "how many Y", "show me Z", "find customers", "what is the count") plus concrete data terms, giving strong coverage of what a user would actually say.

3 / 3

Distinctiveness Conflict Risk

The "data warehouse" / SQL-analysis niche with distinct triggers is unlikely to overlap with other skills, matching the clear-niche anchor.

3 / 3

Total

12

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 3 missing

Warning

Total

15

/

16

Passed

Repository
astronomer/agents
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.