genkit
Build production-ready AI workflows using Firebase Genkit. Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run. Supports TypeScript, Go, and Python with Gemini, OpenAI, Anthropic, Ollama, and Vertex AI plugins.
90
88%
Does it follow best practices?
Impact
92%
1.13xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Quality
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 concrete actions, includes a comprehensive set of natural trigger terms covering the framework, languages, and AI providers, explicitly states both what it does and when to use it, and carves out a distinct niche around Firebase Genkit that minimizes conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'creating flows, tool-calling agents, RAG pipelines, multi-agent systems, deploying AI to Firebase/Cloud Run' along with supported languages and AI provider plugins. | 3 / 3 |
Completeness | Clearly answers both what ('Build production-ready AI workflows using Firebase Genkit') and when ('Use when creating flows, tool-calling agents, RAG pipelines, multi-agent systems, or deploying AI to Firebase/Cloud Run') with explicit trigger guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'Firebase Genkit', 'flows', 'tool-calling agents', 'RAG pipelines', 'multi-agent systems', 'Cloud Run', 'TypeScript', 'Go', 'Python', 'Gemini', 'OpenAI', 'Anthropic', 'Ollama', 'Vertex AI'. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche focused specifically on Firebase Genkit with distinct triggers; the combination of 'Firebase Genkit' with specific workflow types (flows, RAG pipelines, multi-agent systems) makes it highly distinguishable from generic AI or Firebase skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, highly actionable skill with excellent executable code examples covering Genkit's full feature set. The main weakness is length - at 500+ lines it could benefit from splitting detailed reference material (plugin tables, all deployment options) into separate files. The content is well-structured but trades conciseness for comprehensiveness.
Suggestions
Move the Supported Plugins tables to a separate PLUGINS.md reference file and link to it
Trim the 'When to use this skill' section - Claude can infer appropriate use cases from the examples
Consider moving deployment options (Firebase, Express, Cloud Run) to a separate DEPLOYMENT.md file
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is comprehensive but includes some unnecessary verbosity, such as the detailed installation steps for multiple providers and the extensive plugin tables. Some sections like 'When to use this skill' could be trimmed since Claude can infer appropriate use cases. | 2 / 3 |
Actionability | Excellent executable code examples throughout - all TypeScript snippets are complete, copy-paste ready, and cover the full range of Genkit capabilities from basic flows to RAG pipelines and multi-agent systems. | 3 / 3 |
Workflow Clarity | Clear step-by-step sequences for installation, setup, and deployment. The numbered steps in Installation & Setup are explicit, and the code examples show complete workflows with proper error handling (e.g., 'if (!output) throw new Error'). | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections, but the document is quite long and monolithic. The References section links to external docs, but inline content like the full plugin tables and all deployment options could be split into separate reference files. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (679 lines); consider splitting into references/ and linking | Warning |
Total | 10 / 11 Passed | |
- Repository
- supercent-io/skills-template
- Commit
c033769
- Reviewed
Table of Contents
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