developing-genkit-go
Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.
71
88%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
89%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 solid skill description that clearly identifies its niche (Genkit in Go) and provides explicit trigger guidance via a 'Use when' clause with good keyword coverage. The main weakness is that the capabilities are described more as topic areas than concrete actions, which slightly reduces specificity. Overall, it would perform well in a multi-skill selection scenario.
Suggestions
Rephrase capability topics as concrete actions, e.g., 'Creates flows, defines tools, configures model providers, handles streaming responses, and manages prompts for Genkit Go applications.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (AI-powered applications using Genkit in Go) and lists several actions/concepts (generation, prompts, streaming, tool calling, model providers), but these read more like topic keywords than concrete actions. It doesn't list specific operations like 'create flows', 'define tools', or 'configure model providers'. | 2 / 3 |
Completeness | Clearly answers both 'what' (develop AI-powered applications using Genkit in Go) and 'when' (explicit 'Use when' clause covering building AI features, agents, flows, tools, or working with Genkit Go code involving specific concepts). | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords a user would say: 'Genkit', 'Go', 'AI features', 'agents', 'flows', 'tools', 'generation', 'prompts', 'streaming', 'tool calling', 'model providers'. Good coverage of terms a developer working with Genkit Go would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive due to the specific combination of 'Genkit' and 'Go'. This is a narrow niche that is unlikely to conflict with other skills — even other AI framework skills or general Go skills would not overlap significantly. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
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 high-quality skill that efficiently introduces Genkit Go with a working hello world, a well-organized reference table for progressive disclosure, concrete CLI commands, and non-obvious SDK-specific guidance. The main weakness is the lack of explicit validation/error-recovery workflows for common development scenarios, though this is partially mitigated by the simplicity of the primary use case and the delegation to reference files.
Suggestions
Consider adding a brief troubleshooting or validation section covering common failure modes (e.g., missing GOOGLE_API_KEY, plugin init errors) with specific error messages and fixes.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient. It doesn't explain what AI is, what Go is, or how SDKs work. Every section earns its place: a working hello world, a reference table, CLI commands, and key guidance that provides non-obvious, SDK-specific advice (like the jsonschema struct tag tip). | 3 / 3 |
Actionability | The hello world is fully executable and copy-paste ready. CLI commands are concrete with real flags and examples. The key guidance section provides specific, actionable patterns (e.g., 'use jsonschema:"description=..." struct tags') rather than vague advice. | 3 / 3 |
Workflow Clarity | The hello world demonstrates a clear single workflow (init → define flow → serve), and the CLI section shows how to run and test. However, there's no explicit validation or error-handling workflow for common failure modes (e.g., missing API keys, plugin initialization failures, flow debugging). The key guidance is a list of tips rather than a sequenced workflow. | 2 / 3 |
Progressive Disclosure | Excellent progressive disclosure with a clear reference table mapping features to specific files with 'when to load' guidance. The SKILL.md serves as a concise overview with well-signaled one-level-deep references. Navigation is intuitive and organized by feature area. | 3 / 3 |
Total | 11 / 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 |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
metadata_field | 'metadata' should map string keys to string values | Warning |
Total | 9 / 11 Passed | |
- Repository
- firebase/agent-skills
- Commit
c3bb9d5
- Reviewed
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