schema-validator
Schema Validator - Auto-activating skill for Data Pipelines. Triggers on: schema validator, schema validator Part of the Data Pipelines skill category.
33
3%
Does it follow best practices?
Impact
83%
1.07xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/11-data-pipelines/schema-validator/SKILL.mdQuality
Discovery
7%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 description is essentially a template placeholder with no substantive content. It names the skill and its category but provides zero information about what it actually does, what schemas it validates, or what formats/technologies it supports. The duplicated trigger term suggests auto-generation without human review.
Suggestions
Add concrete actions describing what the skill does, e.g., 'Validates data schemas against defined specifications, checks field types, detects missing required fields, and reports schema violations in data pipelines.'
Add a 'Use when...' clause with natural trigger terms, e.g., 'Use when the user mentions schema validation, data contracts, schema drift, field type checking, JSON schema, Avro schema, or pipeline data quality.'
Remove the duplicated trigger term and expand with varied natural language terms users would actually say when needing schema validation.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names 'Schema Validator' and 'Data Pipelines' but provides no concrete actions. There is no mention of what the skill actually does—no verbs like 'validates', 'checks', 'compares', or any specific capabilities. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name itself, and the 'when' clause is just a repeated trigger term with no explicit guidance on when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | The only trigger terms listed are 'schema validator, schema validator' (duplicated). It misses natural user terms like 'validate schema', 'schema validation', 'check schema', 'data schema', 'JSON schema', 'schema errors', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The term 'Schema Validator' is somewhat specific to a niche (schema validation in data pipelines), which provides some distinctiveness, but the lack of concrete details means it could overlap with other data validation or pipeline skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is an empty template with no substantive content. It contains only generic boilerplate that could apply to any skill topic, with no actual schema validation knowledge, code examples, tool references, or actionable instructions. It provides zero value beyond what Claude already knows.
Suggestions
Add concrete, executable code examples for schema validation (e.g., using Pydantic, JSON Schema, Great Expectations, or Cerberus) with specific input/output examples.
Define a clear workflow for schema validation in data pipelines: e.g., 1) define schema, 2) validate incoming data, 3) handle validation errors, 4) log/report results — with explicit validation checkpoints.
Replace all generic boilerplate sections ('Capabilities', 'Example Triggers') with actual domain-specific content such as common schema patterns, error handling strategies, and integration points with ETL tools like Airflow or Spark.
Add references to detailed materials (e.g., a SCHEMAS.md for common schema patterns, EXAMPLES.md for pipeline integration examples) to support progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely filler and boilerplate. It explains nothing Claude doesn't already know and provides zero domain-specific information about schema validation. Every section restates the same vague concept without adding value. | 1 / 3 |
Actionability | There are no concrete code examples, commands, schemas, or executable guidance whatsoever. The skill describes what it could do ('provides step-by-step guidance') rather than actually providing any guidance. | 1 / 3 |
Workflow Clarity | No workflow steps, sequences, or validation checkpoints are defined. The content merely claims it 'validates outputs against common standards' without specifying any actual process or standards. | 1 / 3 |
Progressive Disclosure | The content is a flat, monolithic block of generic text with no references to detailed materials, no links to related files, and no meaningful structural organization beyond boilerplate headings. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
4dee593
- Reviewed
Table of Contents
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