pantheon-ai/ansible-validator
Comprehensive toolkit for validating, linting, testing, and automating Ansible playbooks, roles, and collections. Use this skill when working with Ansible files (.yml, .yaml playbooks, roles, inventories), validating automation code, debugging playbook execution, performing dry-run testing with check mode, or working with custom modules and collections.
Overall
score
100%
Does it follow best practices?
Validation for skill structure
Discovery
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.
This is an excellent skill description that hits all the key criteria. It provides specific capabilities, includes comprehensive trigger terms that Ansible users would naturally use, explicitly states when to use the skill, and is clearly distinguishable from other automation or YAML-related skills through Ansible-specific terminology.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'validating, linting, testing, and automating Ansible playbooks, roles, and collections' along with 'debugging playbook execution, performing dry-run testing with check mode.' | 3 / 3 |
Completeness | Clearly answers both what ('validating, linting, testing, and automating Ansible playbooks, roles, and collections') AND when with explicit 'Use this skill when...' clause covering multiple trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Ansible', 'playbooks', 'roles', 'collections', '.yml', '.yaml', 'inventories', 'check mode', 'custom modules', 'automation code' - these are terms Ansible users naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with Ansible-specific terminology (playbooks, roles, collections, check mode, inventories) that clearly separates it from generic YAML or automation skills. | 3 / 3 |
Total | 12 / 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 demonstrates best practices across all dimensions. It provides comprehensive, actionable guidance for Ansible validation with clear workflows, explicit validation checkpoints, and well-organized progressive disclosure to reference materials. The content respects token efficiency while remaining thorough and executable.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, assuming Claude's competence with Ansible. No unnecessary explanations of basic concepts; every section provides actionable information without padding. | 3 / 3 |
Actionability | Provides fully executable commands throughout with copy-paste ready bash scripts and ansible commands. Includes concrete examples with good/bad code patterns and specific error-solution mappings. | 3 / 3 |
Workflow Clarity | Clear decision tree workflow with numbered steps and explicit validation checkpoints. Includes feedback loops (e.g., 'If molecule fails due to environment... document the blocker but don't fail overall validation') and proper sequencing with validation order explicitly stated. | 3 / 3 |
Progressive Disclosure | Well-structured overview with clear references to external files (references/common_errors.md, references/best_practices.md, etc.). Content is appropriately split between inline essentials and referenced detailed materials with one-level-deep navigation. | 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.
Install with Tessl CLI
npx tessl i pantheon-ai/ansible-validatorReviewed
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