writing-vizro-yaml

Use this skill when writing or debugging Vizro YAML dashboard configurations — component syntax, data_manager registration, custom function wiring, filter/parameter setup, or AG Grid tables. Activate when the user is building a Vizro app, encountering YAML or runtime errors, or asking about Vizro component patterns.

1.73x

Quality

93%

Does it follow best practices?

Impact

92%

1.73x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

87%

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-crafted reference skill that is concise, highly actionable, and well-organized with clear progressive disclosure to a deeper reference file. Its main weakness is the lack of an explicit end-to-end workflow with validation steps for building a Vizro app, though the reference table points to an 'End-to-End Data Flow' section in the deeper file. The critical mistakes list is particularly valuable and domain-specific.

Suggestions

Consider adding a brief 3-5 step workflow sequence (e.g., 1. Register data → 2. Define pages → 3. Build dashboard → 4. Validate with Vizro().build()) to provide workflow clarity for users building apps from scratch.

Dimension	Reasoning	Score
Conciseness	Every section is lean and purposeful. The numbered mistakes list is terse but informative, quick patterns show only essential YAML, and imports are listed without explanation. No unnecessary preamble or concept explanations that Claude would already know.	3 / 3
Actionability	Provides fully copy-paste-ready YAML patterns for the most common components (graph, KPI card, AG Grid, filter), concrete Python imports, and specific anti-patterns with exact fixes (e.g., module prefix format, quoting rules). The guidance is immediately executable.	3 / 3
Workflow Clarity	The skill is primarily a reference/pattern guide rather than a multi-step workflow, but it lacks any explicit sequencing for building a Vizro app (e.g., register data → define pages → build app → run). The 'Critical Mistakes' list implicitly guides but doesn't provide a clear ordered workflow or validation checkpoints.	2 / 3
Progressive Disclosure	Excellent structure: concise overview in SKILL.md with a well-organized table pointing to specific sections in yaml-reference.md. References are one level deep and clearly signaled with searchable section headers. Content is appropriately split between quick reference and deep dive.	3 / 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.

This is a strong skill description that clearly identifies a specific niche (Vizro YAML dashboards), lists concrete capabilities, and provides explicit trigger conditions. The only minor issue is the use of second-person imperative voice ('Use this skill when...', 'Activate when...') rather than third-person declarative, though this is a common pattern seen in good examples from the rubric itself.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: writing/debugging YAML dashboard configurations, component syntax, data_manager registration, custom function wiring, filter/parameter setup, and AG Grid tables. These are concrete, domain-specific capabilities.	3 / 3
Completeness	Clearly answers both 'what' (writing/debugging Vizro YAML dashboard configurations with specific sub-tasks) and 'when' (explicitly states 'Activate when the user is building a Vizro app, encountering YAML or runtime errors, or asking about Vizro component patterns').	3 / 3
Trigger Term Quality	Includes strong natural keywords users would say: 'Vizro', 'YAML', 'dashboard', 'filter', 'parameter', 'AG Grid', 'runtime errors', 'component patterns', 'data_manager'. Good coverage of terms a Vizro developer would naturally use.	3 / 3
Distinctiveness Conflict Risk	Vizro is a specific framework, and the description targets a clear niche — Vizro YAML dashboard configurations. This is highly unlikely to conflict with generic YAML, dashboard, or Python skills due to the repeated Vizro-specific terminology.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

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: mckinsey/vizro
Commit: e1cf317

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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