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database

Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.

49

Quality

54%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/database/SKILL.md

The canonical home for this skill is database in administrakt0r/AI-Agents-Safe-Coding-Skills

SKILL.md
Quality
Evals
Security

Quality

Content

50%Weight 40%Scale 1-5

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

The body is a well-structured 7-phase orchestration overview that routes to other skills via copy-paste prompts, but it relies on generic action steps, lacks validation feedback loops for destructive database operations, and does not progressively disclose detail into separate files.

Suggestions

Add explicit validation checkpoints and feedback loops within the migration and operations phases (e.g., verify integrity, roll back on failure, re-validate).

Make per-phase actions more concrete with specific commands or code snippets instead of abstract hints.

Move the technology workflow and quality-gate detail into reference files linked from the overview to enable true progressive disclosure.

DimensionReasoningScore

Conciseness

Mostly lean with no conceptual over-explanation, but the repeated 5-step action boilerplate and copy-paste prompts that merely echo skill names add padding that could be tightened.

3 / 5

Actionability

Copy-paste prompts give concrete skill-invocation syntax ("Use @database-architect to..."), but the per-phase action steps are abstract hints ("Analyze slow queries", "Optimize indexes") with no commands or code.

3 / 5

Workflow Clarity

Phases are clearly sequenced with numbered actions, but migration and operations phases involve destructive/batch database work without explicit validate→fix→retry feedback loops, capping workflow clarity at 3 per the rubric.

3 / 5

Progressive Disclosure

Well-organized into headed sections but entirely self-contained with no external file references and no bundle files present, so there is no progressive disclosure via referenced materials.

3 / 5

Total

12

/

20

Passed

Description

58%Weight 40%Scale 1-5

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 clearly scopes a database dev/ops niche and lists several relevant activity areas, but it lacks an explicit "Use when" trigger clause and relies on somewhat abstract keywords rather than concrete user phrasings.

Suggestions

Add an explicit trigger clause, e.g. "Use when designing schemas, running migrations, optimizing queries, or building data pipelines."

Include more natural user-facing trigger terms and synonyms (queries, indexes, schema, performance tuning, .sql).

Reframe the activity list as concrete verbs (design schemas, run migrations, optimize queries) rather than abstract nouns.

DimensionReasoningScore

Specificity

Names the database domain plus several concrete activity areas ("SQL, NoSQL, database design, migrations, optimization, and data engineering"), giving broad coverage, though they are abstract nouns rather than concrete verbs.

4 / 5

Completeness

Provides a clear "what" (database dev/ops workflow covering listed areas) but has no "Use when..." or equivalent explicit trigger guidance, capping completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

Includes relevant natural-ish terms (SQL, NoSQL, migrations, optimization, data engineering) but misses common user phrasings and synonyms like queries, indexes, schema, or performance tuning.

3 / 5

Distinctiveness Conflict Risk

The database-specific framing is mostly distinct with only minor overlap risk against adjacent data-engineering or cloud-devops skills.

4 / 5

Total

14

/

20

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

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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